Policy paper - BICEPS · 2013-04-15 · 3 Editorial This issue continues our series of policy...

Policy paperWhere is demography leading Latvian higher education? Zane Cunska

ArticlesThe impact of EU Cohesion policy on environmental sectorsustainability in the Baltic states Sirje Pädam, Üllas Ehrlich, Koidu TennoCredible commitment and cartel: the case of the Hansa merchant in the guild of late medieval Tallinn Kaire PõderIndustry relocation, linkages and spillovers across the Baltic Sea: extending the footloose capital model Ole Christiansen, Dirk H. Ehnts, Hans-Michael Trautwein

Book reviewEconomic prosperity recaptured: the Finnish path from crisis to rapid growthSeppo Honkapohja, Erkki A. Koskela, Willi Leibfritz, Roope Uusitalo José R. Sánchez-Fung

PhD news

Volume 10 Number 1 Spring 2010

Baltic Journal of Economics Volum

e 10 Num

ber 1 Spring 2010

Baltic Journal of Economics

EditorsAlf Vanags, Baltic International Centre for Economic Policy Studies

Anders Paalzow, Stockholm School of Economics in Riga

Editorial BoardRaul Eamets, Tartu University

Kenneth Smith, Millersville UniversityTorbjörn Becker, Stockholm Institute of Transition Economics

Karsten Staehr, Bank of EstoniaKonstantins Benkovskis, Bank of Latvia

Igor Vetlov, Bank of Lithuania Nerijus Maciulis, ISM University of Management and Economics

Managing EditorZane Cunska, Baltic International Centre for Economic Policy Studies

Publisher: Baltic International Centre for Economic Policy Studies jointly with Stockholm School of Economics in Riga.

Editorial address: Baltic International Centre for Economic Policy Studies, Strelnieku iela 4a, Riga, LV-1010, Latvia; www.biceps.org/bje; e-mail: [email protected].

The Baltic Journal of Economics is a semi-annual refereed scientific journal in economics. The Journal is intended to provide a publication medium for original research in economics and selected fields for scholars working in the Baltic countries or those who are working with topics relevant for the Baltic countries or for transition economies in general. Papers may be theoreti-cal or empirical in their emphasis and with relevance to the Baltic countries. Papers with policy relevance or which combine economic theory with empirical findings are particularly welcome.

Abstracting and indexing: EconLit, the Journal of Economic Literature electronic edition/CD-ROM, EBSCO, Scopus, GESIS, SSCI, Cabell’s directory and RePec.

Submissions: electronic submissions of manuscripts should be addressed to: [email protected]. Instructions for authors see on www.biceps.org/bje.

Subscriptions: For subscriptions please contact the Managing Editor on [email protected] 1406-099X

Content

Editorial 3

Policy paper Where is demography leading Latvian higher education? 5 Zane Cunska

Articles The impact of EU cohesion policy on environmental sector sustainability in the Baltic states 23 Sirje Pädam, Üllas Ehrlich, Koidu Tenno

Credible commitment and cartel: the case of the Hansa merchant in the guild of late medieval Tallinn 43 Kaire Põder

Industry relocation, linkages and spillovers across the Baltic Sea: extending the footloose capital model 61 Ole Christiansen, Dirk H. Ehnts, Hans-Michael Trautwein

Book review Economic prosperity recaptured: the Finnish path from crisis to rapid growth 79 Seppo Honkapohja, Erkki A. Koskela, Willi Leibfritz and Roope Uusitalo José R. Sánchez-Fung

PhD news Managementbyvalues:analysisofinfluencingaspectsanditstheoretical and practical implications 83 Krista Jaakson

Manifestations of organizational culture based on the example of Estonian organizations 85 Anne Reino

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Editorial

This issue continues our series of policy papers on higher education in the Baltic countries that started with the 2009 spring issue. This issue’s paper examines the policy implications and responses of the demographic shock that is about to hit Latvian higher education. This is a topic of high relevance not only in Latvia but all over Europe and the paper offers an inter-esting contrast between the Latvian and Estonian responses. We have a mix of regular papers: an interesting interpretation of the Hansa guild in terms of game theory; an application of the footloose capital model; and an evaluation of the impact of cohesion policy on environment sector sustainability in the Baltic states.

We would also like to thank our benefactors, the Anne-Marie and Gustav Anders stiftelse för medieforskning and the Bank of Latvia for their continued support of the Journal for 2010.

Anders Paalzow Alf Vanags

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Where is demography leading Latvian higher education?

Zane Cunska1

1. Introduction

Higher education in Latvia in the last two decades has been characterized by major expansion, oftenreferredtoasthe“massification”ofhighereducation.Thusbytheearly2000sthenum-ber of students per 10000 population had more than tripled as compared to the early 1990s. So far the growth in enrolment rates has been associated with both positive demographic trends and increasing accessibility of higher education (via access to study loans, wide selec-tion of study forms and programmes). However, demographic development poses growing concerns about the future of higher education in all developed countries. Most European countries are facing an unprecedented ageing of their populations, with ageing and depopula-tion hitting the Eastern European countries, including Latvia, especially hard. In the years tocome,significantexpansionoftheyoungerpopulationisnotprojectedinanyEuropeancountry (Eurostat, EUROPOP2008). Quite the opposite – the younger cohorts are decreasing in size. As a consequence, an impact on the education system is inevitable.

Little seems to have been done to investigate the consequences of demographic decline on the higher education system and to identify the actual scope of the problem. The aim of this article is to analyze the demographic potential of higher education in Latvia and to sketch the most likely enrolment volume in the medium term future. Associated policy issues are described.

This paper is organized as follows. The second section gives background information – de-mographic facts and enrolment trends in recent years. The third section presents enrolment projections for Latvia, suggesting three scenarios that represent a set of plausible alternative outcomes based on changing environment and circumstances. The fourth section outlines policy issues arising for higher education and recommendations for addressing them. The last section concludes.

2. Facts and figures

The demographic situation in Latvia is characterized by a negative natural rate of increase and by ageing. Depopulation started in the early nineties and still continues. In particular, the size of younger age cohorts has decreased. This is connected to the fact that at the beginning of the nineties the birth rate fell sharply. Eighteen to twenty years later the smaller youth population is about to enter the higher education system and the labour market. As evident

1 Baltic International Centre for Economic Policy Studies and University of Latvia, Strelnieku iela 4a, Riga, LV-1010, email: [email protected].


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from the population projections (Figure 1), the population aged 15-24 will fall by about 40% in the coming 10 years, and will remain low in the foreseeable future. This fact has to be seen in the context of previous experience of a rising younger population associated with high birth rates in the nineteen eighties.

Figure 1. Youth population (15-24 years) projections for Latvia

Source: Eurostat population projections (EUROPOP2008)

Latvian higher education has already started to experience this decline. In the 2009/2010 academicyeartheLatvianHEsystemforthefirsttimeexperiencedasignificantfallinnum-bersofstudents.Totalenrolmentdecreasedby10%,withthenumberoffirstyearbachelorstudents down by 26% compared to the year before.

According to statistics on the number of students per 10 thousand inhabitants – 492 in 2009/2010 (Figure 2), Latvia is among the highest in the world together with Finland, the UK, and Canada. There were as many as 566 students per 10 thousand inhabitants in 2006/2007,

Figure 2. Number of students per 10 000 inhabitants in Latvia

Source: Ministry of Education and Science, Latvia

Baltic Journal of Economics 10(1) (2010) 5-21

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and this indicator has been increasing since 1993 when the expansion of HE started. Some decreasewasseeninthe2008/2009schoolyear,butasignificantdeclineisclearlyvisiblein2009/2010.

This HE expansion motivated creation of a great number of HE institutions, both public and private. There are now 60 HE institutions in Latvia (2009), which is very high for just 2.2 mil-lion inhabitants (27 per 1 million inhabitants). This compares with Estonia (29) and Denmark (32),whicharealsosmallcountries,butsignificantlyexceedstheUS(14),theUK(15),theNetherlands (10) and Germany (8), which, in contrast to Latvia, host many foreign as well as home students.

Fromagespecificenrolmentratios,i.e.theratioofstudentsintherespectiveagepopulationgroup in Latvia, we see that naturally the highest proportion of students is in the 19-24 age cohorts²(seeFigure3).Startingfromage23andolder,agespecificenrolmentratesgradu-ally decrease with every older cohort – for the 25-28 age cohorts it is in the 8-13% area, for 29-39-year-olds the ratio is 5%, but in the older age groups 40-plus – slightly above 1%. The observed expansion of HE has happened in both the younger groups, and the older groups. In particular, the 29-39-age cohort that started as low as 1% in 1998 (there were virtually no adults above 30 in HE) has grown to 5% in 2010. Additionally, the number of students over


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Source: Ministry of Education and Science and Eurostat, author’s calculations

2 The changes in the 18-year-old enrolment rate are connected to structural changes in the secondary education system and the transition from 11 to 12 years schooling (primary + secondary) starting in 1991. As a consequence, schooling before tertiary education takes longer, and the number of 18-year-old students has decreased.

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40 has risen from 0.3% in 1998 to slightly above 1% in 2010, but still very few students are over 40.

Between 1998-2008, enrolment trends showed unambiguous stable growth both in absolute and relative terms. In the 2009/2010 academic year the situation has changed – enrolment has fallen in all age groups. Naturally, this raises the question of what developments to expect in the future.

3. Evidence from elsewhere

According to World Bank estimates (Chawia, 2007), by 2025 in Latvia the number of pupils inprimaryschoolswillshrinkby25%,insecondaryschoolsby20%,butthemostsignificantfall is expected in the number of students in higher education – by 40%. Mizikaci (2007) has examined the phenomenon of the shrinking youth population in Europe and the associated effects on higher education. She notes that the severest declines will be observed in Estonia, Latvia, and Slovenia, where more than half of the 18-23 age group in 2005 will disappear by 2050. For those countries, immigration would not be enough to compensate for the natu-ral decline, especially because currently they record negative net migration (i.e. emigration for Latvia, Lithuania, Poland, zero net migration for Estonia). In all former Eastern bloc countries, higher education is at risk because of low fertility rates and emigration, as well as failuretoenrolsignificantnumbersofforeignstudents.FollowingdiscussionsattheSalzburgseminar on the future of higher education, Baumgartl (2007) states that due to shifting de-mographics in Europe some HE institutions will suffer from lack of students in the very near future,andthat“thepresentandfuturebodyofHEpopulationshouldbeexamined”.

Before 2009 the effects of demography on the tertiary education system in Latvia had not been explicitly studied. Within the EU Structural Funds funded Ministry of Welfare labour market research programme (2005-2006) one project studied graduate life paths and study outcomes, another project modelled labour market developments, while another project stud-ied conformity of HE programmes with labour market requirements, but no explicit attention was paid to investigating demographic impacts. In the spring of 2009, the Ministry of Educa-tion and Science communicated that in the nearest seven to ten years the number of students will continue to diminish, and in the 2015/2016 academic year the number of students will decrease by a third compared to recent years (LETA, May 26 2010).

Occasionally the issue of demographic effects on the higher education system has been men-tioned in the media, where (most often) university representatives are cited expressing con-cerns about the falling number of secondary school graduates. Overall, these are the same higher education establishments where the issue is raised and discussed, usually in the form of guessing, since it is crucially important for their development strategies. In the context of writing the Latvian sustainable development strategy, some analytical discussions on the issue have taken place over 2008-2010. None of them has been based on or resulted in a research paper.

The most comprehensive analysis of tertiary education demography has been performed by the OECD, which in a report (OECD, 2008) concludes that “demography has only recently become a concern in debate on higher education policy, and past growth of systems in OECD


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countries has had little to do with demographic changes. The increase in rates of admission to highereducationhasbeenofgreaterimportancethanthesizeofagecohorts.”(TeichlerandBürger, OECD 2008, Chapter 5). Among other things, the report concludes that: (1) student participation will continue to expand and will in most cases be evident from growth in the size of higher education systems. Contraction will affect only a small number of countries; (2) women will be in the majority in the student population; (3) the mix of the student popula-tion will be more varied, with, e.g., greater numbers of international students, older students, and those studying part-time; (4) the social base in higher education will probably continue to broaden. Latvia, not being an OECD country, is not analyzed in the report. With domestic knowledge about the Latvian HE system, we have reason to think that Latvia may be among the countries affected by contraction, but this will be analyzed later in the paper.

4. Methods

For projecting future developments, the approach taken in this paper is the enrolment-ratio method, which is common for estimating sub-populations and uses two components –readily available population projections and enrolment rate development trends both (1) extrapolated from statistically observed ratios, and (2) estimated based on expert opinions and peer experi-ence. For discussion regarding choice of projection method, see Cunska (2010).

The OECD (2008) report on the future of higher education uses similar trend extrapolation methodology and argues that it is the turning points that in fact play the most important role in demographic trends, concluding that demographic trends cannot be extrapolated directly, but only explored through forward-looking scenarios incorporating political and economic factors. The projection approach used in the OECD report uses UN population projections as a basis and calculates enrolment with the extrapolated trends.

Ahuja and Filmer (1995) adopted a very similar approach by taking existing UN population projections and superimposing onto them an educational distribution estimated for two broad age groups (ages 6-24 and 25+) from a given set of enrolment ratios and UNESCO projec-tions.

Three development trend scenarios are developed here: a stable enrolment ratio scenario, a global education trend scenario, and a crisis scenario. The different scenarios represent a set of plausible alternative outcomes based on changing environment and circumstances. The first two variants can be thought of as rather statistical,whereas the third scenario reliesmostly on expertise and knowledge in the area.

For cohort size, the Eurostat population projections (EUROPOP2008) convergence scenario is used. This describes possible future demographic developments assuming that across Eu-ropeancountriesfertilityandmortalityconvergetothoseofthe“forerunners”by2150.Theperiod for projections used is 2010 – 2020. The projections already take account of birth, death, and migration rates, and we assume rates equal for population in and outside tertiary education. The model inherits all the assumptions made for the projections.


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5. Scenarios

The stable enrolment ratio (SER) scenario represents a situation in which tertiary educa-tion develops smoothly into the future. The only changes arise from differences in cohort size. Observed trends over the years 1998-2010 are extrapolated for the following 10 years, assuming that:

• The proportion of students in the respective age cohort will continue to change at the same average speed and direction as previously.

• Transition rates and dropout rates will change as previously.• Growthconvergestozerowhentimeconvergestoinfinity.

All calculated trends are positive or virtually constant (Appendix, Figure A1). Growth is ex-pected in the ratio of younger students (20-23) and of the non-traditional age group, (29-39). The proportions of students in the 24-28 and 40-plus age groups are assumed to remain stable at their 2010 levels.

Figure 4. Observed (1998-2010) and projected (2011-2020) number of students in tertiary education – stable enrolment ratio scenario

Source: Eurostat, author’s calculations

This scenario suggests that the total number of students in tertiary education will decrease from 113 thousand in 2010 to 92 thousand in 2020, while enrolment in 2020 would be 80% of that of 2010 (Figure 4). The most severe decline will be observed in the traditional student age groups (17-24) – by 44%, whereas the size of older student age groups (29 plus) will remain stable and would even slightly increase compared to the 2010 level as a result of posi-tive enrolment ratio trends and slightly increasing cohort size. The share of older students (over 29) will increase from 24% to 44%.


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The global education trend (GET) scenario takes into account schooling patterns across European countries and assumes that:

• In the years 2010 – 2020 the enrolment ratio age structure in Latvia converges to the EU-27 average.

• The speed of convergence depends on the size of the difference between the rate in the previous period and the target value (EU-27 average).

Enrolment ratios in the EU-27 have been gradually rising during 1998-2005, and have stabi-lized since 2005. They are generally lower than the Latvian 2010 rates, so that all but 25 and 26 year-old rate trends are negative (Figure A2 in Appendix).

Figure 5. Observed (1998-2010) and projected (2011-2020) number of students in tertiary education – global education trend scenario


According to the GET scenario, a decline in higher education participation at all ages is expected (Figure 5). Total enrolment in 2020 is expected to approach the level of 1998 at around 70 thousand students – a decline of 38% compared to 2010 enrolment. It also entails a reduction of over 50% in traditional age student numbers. The older cohorts (29 plus) are not yet declining by 2020, and the fall in enrolments is only affected by convergence to the lower EU enrolment rate assumption. This results in a 13% fall in enrolment. As a result, the student population will be older and the proportion of non-traditional students in the total student population will increase to 50% in contrast to 36% in 2010.

The crisis (CRI) scenario is designed to capture possible other effects that do not follow from statistics but can be concluded from the literature on historical development in other coun-tries, the author’s observations of the situation, and suggested developments by experts. This


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scenario is the most subjective of the three and is intended to sketch general developments on topofthosedirectlyflowingfromdata.

During recession, some individuals invest in graduate education to position themselves for a better job when the economy revives. Often people change their life plans to apply for Master or PhD programmes earlier than planned because of unfavourable labour market conditions and because alternatives to schooling are less attractive. This behaviour can be observed from two relatively recent historical trends for recessionary periods in the global economy: 1991-1993 and 2000-2002. It was observed that enrolment grew more rapidly during and after recessions, while the largest dips happened in boom years. However, a slowdown in enrol-ment was observed at the very beginning of recession (Moody’s International Public Finance (2009), data on Canada, France, Italy, Spain, the UK, and the US).

In its report, Moody’s outlines that universities are expected to experience some stress but be more sheltered than other sectors from the global recession. “This is due to their counter-cyclical business aspects, government support, and growing role in economic development and rebuilding.”However,many face the conflictingpressuresof risingdemand for theirservices while also needing to adjust to a weaker funding outlook.

Hazarika (2002) investigated the effects of regional recessions on enrolments in the US and found that wealthier students are more likely to attend college in a recession, whereas those from less wealthy families are affected by credit constraints and less likely to attend college. Accesstofinancingthereforeplaysaroleinenrolmentdecisions.InFinlandinthe1990crisisperiod, applications for higher education grew by about 25%, and participation in entrance examinations by 42% (Kivinen and Rinne, 1996). The increased interest, though, was not supportedbyasufficientincreaseinthesupplyofstudyplacessoactualenrolmentsremainedstable.

The impact on a particular country and particular institutions may vary. In the Latvian situa-tion some additional institutional and behavioural aspects would play a role:

• Participation in tertiary education will be a function of people’s beliefs on the speed of recovery of the economy. If people believe in a fast recovery (2-3 years), i.e., believe they will have job, they are willing to invest in education and probably even bear considerable personal cost. In the opposite situation, where people believe in slow recovery or stagna-tion, they may leave the country for study or work. The emigration alternative is relatively easy given the open EU labour market.

• Completion of some degree of tertiary education is already a minimum standard for cer-tain types of employment (government sector, schools), and therefore enrolment (and graduation) rates were very high by international standards even before the recession. There is hardly more room for growth in enrolment rates due to a saturated local market.

• In Latvia, simultaneous work and study practice is common (Auers, Rostoks, Smith, 2007), often resulting in prolonged study time (academic breaks, longer programmes). With loss of employment or fewer working hours, study time may actually shorten, so that total enrolment will be lower.

• Reasonsfornotcontinuingstudiesarefinancialproblemsandinabilitytopaystudyfees;shortage of money can also prolong study time as students may be forced to take study


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breaks because of inability to pay tuition fees.• ApopularviewamongtheLatviangeneralpublicisthatanincreaseinqualificationsand

skillslevelsdoesnotsignificantlycontributetoeconomicgrowthandhencepeoplemaynot be willing to invest in education under budgetary pressure (DnB NORD Latvijas barometrs, March 2010).

We take into account that individual behaviour is affected by changes in the labour market in a recession – a loss of job can serve as a catalyst for career decisions. Unchanged educa-tion policy in the country is assumed in this scenario: higher education still relies on local demandandactiveforeignstudentattractiondoesnottakeplace;nofurthersignificantcutsinfinancingtoHEtakeplace,butalsononewinvestment.Weassumepeoplebelievetheeconomy will return to growth in three years. In this scenario, projections are made for more aggregated age groups (Table 1).

According to this scenario, the crisis would have a short-term positive impact on enrolment rates, which will slightly increase above the 2010 level and stay there between 2011 and 2013 (Figure A3 in Appendix). A rise would be expected in the 25-28 age group. After 2013 enrol-ment rates will start to fall to the EU-27 level.

The total number of students in the period 2011-2013 would increase compared to 2009 and 2010 levels, but would not reach the 2006 peak of 131 thousand students. The 25-28 year student group would remain roughly the same size throughout the entire period 2000-2020. After 2013 enrolment rates are expected to converge to the EU average, and the demographic

Age Rationale Assumption

17-24 Most mobile of all groups, also the most free in terms of family commitments. Under crisis: the highest proportion leaving the country (for study and/or work) compared to other groups. Employment (traditionallypopularamongstudentsinLatvia)increasinglydifficulttofindforyoungerpeoplewithoutexperienceanddegree.Peoplestayingin Latvia invest time in education in the belief of recovery, may be more selective regarding the study area and more demanding.

The two effects (emigration anddifficultyinfindinga job) offset each other, enrolment rate is at the pre-crisis level (2008) for 3 years, converges to EU-27 average after 2013, i.e., falls.

25-28 More commitments (family, social, work), consequently emigration is more complicated. More prone to stay and use all local opportunities. In case of loss of job, ready to invest in education but selective regarding the programme. Could choose good quality business education, probably looking for shorter 2-3 year executive education. Thosewhohavedroppedoutcouldgobackandfinishtheirdegree.Those who postponed a decision on second level higher education may start now.

Forthefirstthreeyearsenrolment rate increases by 15% compared to 2008, converges to EU-27 average after 2013.

29 plus This group is most settled of all. They may see little return on investment in a degree, but are probably more likely to attend qualificationcoursestobuildonpreviouseducation.Someproportionmay consider second level tertiary education but with emphasis on professional skills.

Enrolment rate remains con-stant (for different reasons than for 17-24 population) over the first 3 years, con-verges to EU-27 average after 2013.

Table 1. Summary of reasoning and assumptions regarding educational behaviour for sepa-rate age groups


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decline is even more prominent. As a result, the total number of students in 2020 will fall to 81 thousand with less than half (47%) being in the traditional age group (17-24).

Figure 7. Comparison of estimated trends – total number of students in tertiary education according to the three alternative scenarios



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In comparison, all variants indicate a very similar future enrolment situation despite relying on different assumptions about enrolment rate future development. All variants suggest a significantfallintotalenrolment–by18%inSER,by38%inGET,andby28%inthecaseof the CRI scenario compared to 2010 (Figure 7).

The crisis scenario is the only case where enrolment is expected to increase in the short term, and it may turn out to be the ‘best’ case for the higher education system in the nearest future.The other common characteristic concerns changes in student age structure. The number of traditional age students will decrease to somewhere between 44% and 50%. Consequently the traditional age students would be a minority in the student population. In contrast, the proportion of adult students will rise from 24% in 2010 to somewhere between 33% and 44% in 2020 (by a factor of three or four compared to 11% in 1998).

6. Implications for policymaking

The higher education system has to adjust to two imminent changes arising from demograph-ic changes – a decrease in total enrolment volume and a change in the age structure. In its current form the present size of higher education system is not sustainable. Clearly, there are no solutions to increase the size of cohorts as a way to rescue the higher education system, at leastnotinthenearestfuture.Demographicprocessesareinertcomparedtofinancialmarketsand the economy, so there are no quick solutions in demography.

Thefirstquestiontobeaskedis:Shouldthecurrentsystemberescuedbypreservingthecur-rent volume of higher education? Furthermore, is it a problem that there are fewer students, there would be fewer universities, fewer academic staff, less taxes paid, but also less public expenditure on education? Not necessarily. Higher education may be viewed as a service that isinlessdemandandthereforeover-supplied,analogoustophotofilmdevelopmentserviceswith the introduction of digital cameras, or typewriting when computers appeared. In other words, the higher education sector is like any other sector of the economy be subject to a demand side shock reducing the demand for its services to where it was in the 1990s. Among other things this would also imply cost savings to the state budget or alternatively the spend-ing per student can increase without increasing the overall higher education budget.

An obvious way to adjust would be to cut the supply, i.e. to reduce the number of higher education institutions. Here it makes sense to distinguish between private and state institu-


Table 2. Comparison of scenarios: total number of students and proportions of wider age groups


Year 1998 2010 2020 2020 2020Actual Actual SER GET CRI

Proportions of age groups in total number of students17-24 73% 64% 44% 50% 47%25-28 16% 13% 12% 16% 17%

29 plus 11% 24% 44% 33% 36%

Total 70233 112555 92152 69434 80841

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tions, respectively. The private institutions, being to a large extent directly subject to the market mechanisms, might adjust by itself when some might go out of business due to lack of students whereas others might develop new programmes or targeting non-traditional stu-dents. The state-funded institutions, on the other hand, are not directly affected by the market mechanisms since their development to a large extent is determined by political decisions. Based on the demographic changes the state-funded should be restructured, with the lowest performing programmes and institutions simply being closed down. From a political point of view, this might be easier said than done since higher education policy usually are consid-ered as an integral part of other policy programmes, e.g. regional development. Furthermore, thecurrentfinancingmodelofstate-fundedhighereducationinstitutionsmightfurthercom-plicatethenecessaryrestructuring.Giventhefinancialincenctivesprovidedbythecurrentsystem where each student enrolled represent a substantial source of income, there is a great risk that the institutions will lower standards in order to enrol and keep as many students as possible.

Thealternativeapproachtocuttingthesupplywouldnaturallybetofindwaystoincreasethe demand for the services that could be provided by the Latvian higher education sector. This require somewhat of a change of the mindset of policy makers as well as university leaders – to stop thinking of higher education as a cost to bear, but perceive it as a productive and competitive sector of the economy, capable not only of educating people for the Latvian labour market, but also of exporting its services and possibly also educating foreign young people for the Latvian labour market. The demographic decline not only affects the student population, but also the labour market, and working age people will be needed to cope with an increasing old-age dependency problem where opening up the Latvian labour market to foreigners could be at least part of the solution.

The issue of increasing the demand for higher education in Latvia is partly addressed in the work of a specially established group which in December 2009 published an Informative Reporton the structural reforms in higher education and science needed to increase Latvian international competitiveness (Ministry of Economics, 2009). The proposed reforms have three aims: (1) to produce internationally competitive graduates, (2) to supply education that corresponds to the needs of the economy, and (3) to ensure that internationally competitive scientificresultsaresuccessfullytransmittedtotheLatvianeconomy.AccordingtotheRe-port, one of the indicators of successful structural reforms is “proportion of foreign students exceeds10%ofstudentnumbers”by2015(p15).Thisseemstobeaveryambitioustargetin the light of international experience. In this context an Action Plan was developed by the Ministry of Education and Science in the spring of 2010 to implement the above reforms. One of the four main action directions is “internationalization of higher education and in-creasingitsexportcapacity”,i.e.directlyrelatedtoincreasingthedemand.Itrecognizestheimportance of and need to attract foreign students as a way to improve the situation in the higher education sector. The Action Plan is less ambitious than the Report and aims for just a 3% share of foreign students (p15). Is even this target realistic? In 2009/2010 there were 1715


3InformatīvaisziņojumsparnepieciešamajāmstrukturālajāmreformāmaugstākajāizglītībāunzinātnēLatvijasstarptautiskāskonkurētspējaspaaugstināšanai,MinistryofEconomics,Riga,December2009.

4 Pasākumuplānsnepieciešamajāmreformāmaugstākajāizglītībāunzinātnē2010.-2012.gadam,Ministryofeducation and science of Latvia, available at http://www.mk.gov.lv/lv/mk/tap/?pid=40173173.

17

registered foreign students in Latvia (1.5% of the total number of students). Of those, 816 - or 48% - held Russian, Ukrainian, or Lithuanian passports. Clearly, the biggest proportion of those students is likely to be Latvian residents who have lived all their lives in Latvia and acquired a secondary education in Latvia. The term ‘foreign student’ is therefore somewhat inappropriate. Some 400 Erasmus students studied in Latvia in 2009/2010. These of course are genuine foreigners, but do not bring income to Latvian institutions. The real ‘de facto’ foreign student number is therefore much less than reported.

Even nominally (in contrast to real foreigners arriving to study), reaching the goal of 10% or even 3% foreign students may be tricky. In European Higher Education Area countries (Bo-logna countries) on average there are 3.5% foreign students, and 6.6% is the EU-27 average. Countries with the highest proportion and total number of foreign students are those with historically established university traditions (2006: UK – 18.3%, Austria – 15.6%, France

– 14.6%, Belgium – 14.3%, Germany – 12.8%) and where education is in global languages (English, French, German). Other countries are lagging behind, and there is none except Sweden where the proportion of foreign students exceeds 10%.

ItseemsthatthecallforthenecessityforEnglishlanguageprogrammesisfinallybeingheard,as this is a tool to make studies in Latvia accessible to foreigners (see report and action plan mentioned above).Currently there is at least a discussion that provision of programmes and courses in English should be expanded. But is it enough?As noted earlier, shrinking genera-tions is not a uniquely Latvian problem. Similar developments can be observed throughout Central and Eastern Europe. Other countries (like Estonia) are acting fast. For example, while in Latvian Bachelor programmes only basic English is taught, the University of Tartu, from academic year 2010/2011, has launched a new bachelor study programme in Business Ad-ministration that is entirely taught in English, and there are twelve master degree programmes in English (including joint degrees). Estonians have also been active in promoting Estonian education in China. As a result, the proportion of foreign students in Estonia already ex-ceeded 4% in 2008. It is entirely possible that Tartu will attain a critical mass of foreigners and become a regional education centre leaving no space for an alternative centre in Riga. For economics and business studies Latvia is, with few exceptions, already far behind.

Little attention has been paid to addressing the other demographic effect – the ageing popula-tion and the following old age-dependency problem. Here the demographics at least to some extent work in favour of higher education. An ageing population will most likely increase the demand for further higher education during an individual’s work life, i.e. Life Long Learn-ing, since there will be less young people entering the labour market bringing in the most recent knowledge etc. Furthermore, an ageing population will most likely put pressure on the policy makers to increase the retirement age and thereby increasing the number of years an individual is active in the labour market, which in turn should further increase the demand for higher education among the non-traditional groups. In the analysis of the different scenarios above,itwasassumedthattheenrolmentrateforthegroup“29plus”wouldconvergetotheEU27averageafter2013.However, this is something thatcoulddefinitelybe influencedthrough policy making. An active Life Long Learning policy with the aim, not to ‘rescue’ higher education, but with the aim to strengthen the competitiveness of the Latvian economy in the light of its rapidly changing demographics, would certainly increase the enrolment rate among the non-traditional (29 plus) cohorts. One immediate consequence would be that the


18

student body will not be dominated by young kids fresh out of school. They will be mature people,probablymoreconfidentanddemanding,lookingformorepracticalandapplicableknowledge. Needless to say, this will require rethinking the curricula as well as of the way studies are organized. If successful, the concept of Life Long Learning will acquire real meaningandsubstance.Akeyissueiswhetherthestatefundedinstitutionshavetheflexibil-ity to accommodate this new ‘market’ or whether the lion’s share of it will be captured by the privateinstituionswiththeirmoreflexibleorganisationsandgovernancestructures.

7. Conclusion

This paper discusses the implications for higher education in Latvia arising from chang-ing demographics. So three possible variants based on different assumptions were presented. Higher education in Latvia is facing big changes due to the rapidly changing demographics in the years to come. Exact predictions are impossible given the number of different non-demographic impact factors and the unclear economic situation. All the analysis suggests that under any development scenario the total enrolment will fall. Enrolment will in the foresee-able future never be as high as it was in the early 2000s. By 2020 the number of students in higher education will decrease by 18-38 percent under the alternative scenarios. This implies that the current number of higher education institutions cannot be sustained.

Most likely, tertiary education will continue to rely on local demand for education. Even if the export of higher education is stimulated via accessible programmes (especially the lan-guage of instruction), legislation changes and marketing, keeping the present enrolment level is unlikely to be feasible. To illustrate, in order to compensate for shrinking local demand (for example as given by the Stable Enrolment Scenario), by 2020 Latvia would have to attract some 20 thousand foreign students. This means that the number of foreigners in universities would have to rise by a factor of 12 as compared with 2009.

Nearly all developed countries are experiencing the ageing of their populations and shrink-ing youth cohorts (although at a less dramatic rate than in Latvia); therefore the competition for students internationally is becoming more severe. The real issue therefore is not about competition between universities in Latvia, but about the competitiveness of Latvian higher education internationally in order to keep talented Latvian students in Latvia (to prevent a brain drain) and to attracted talanted foreign students.

Informed policy decisions will be required in order to cope with the foreseen oversupply of higher education. There will, for example, be a need to restructure higher education by clos-ing down certain universities, merging programmes, and concentrating resources to attain better quality. There is no (fast) medicine for treating the effects stemming from the rapidly diminishing cohorts. However, there are ways to prevent the higher education system from total collapse following the rapid fall in the demand for its services. A natural way would be to consider the higher education sector beaing a service sector like any other and hence try to identify new markets and services (programmes) to be provided by the educational sector. In this case the ageing population provides an opportunity since it most likely will put more of a policy focus on Life Long Learning. However, Life Long Learning as such is not the remedy – it has to be accompanied by insightful and forward looking policy making accom-panied by a willingness from the side of the higher education institutions to adopt to the new


19Where is demography leading Latvian higher education?

demographic environment and hence to the demands of the ‘non-traditional’ students whose share of the student body will incarease in the future.

References

Ahuja V., Filmer D. (1995). Education Attainment in Developing Countries. New Estimates and Projections Disaggregated by Gender, World Bank Policy research working paper No.1489 (WPS-1489), The World Bank

AuersD.,RostoksT.,SmithK.(2007).FlippingburgersorflippingPages?StudentEmploy-ment and Academic Attainment in Post-Soviet Latvia,Communist and Post-Communist Studies, 2007, 40, pp.477-91

Baumgartl, B.(2007) Relevant Terms of Discussion in Eastern Europe. From Here to There: Mileposts of European Higher Education, Baumgartl, B.Mizikaci, F., Owen D. (eds.). Navreme publications, Vol7b, March 2007, pp 20-21 (available at www.navreme.net)

Chawia, M. et al. (2007). From Red to Grey. Washington, DC: The World Bank, pp 217-261Cunska, Z. (2010).Augstākajā izglītībā studējošo skaits un prognozes Latvijai, Latvijas

UniversitātesdoktoranturakstukrājumsDombrovsky V. (2009). Is anything wrong with higher education in Latvia? Baltic Journal of

Economics, Vol9 No2, Autumn 2009, RigaEurostat, methodological note on EUROPOP2008 convergence scenario, http://epp.eurostat.

ec.europa.eu/cache/ITY_SDDS/EN/proj_08c_esms.htm (accessed 26/10/2009)Hazarika G. (2002). The Role of Credit Constraints in the Cyclicality of College

Enrolments,Education Economics; August 2002, Vol. 10 Issue 2, p133-143, 11pHigher Education to 2030, Volume 1, Demography, Centre for Educational Research and

Innovation, OECD, 2008Kivinen O., Rinne R. (1996). Higher Education, Mobility and Inequality: The Finnish Case,

European Journal of Education, Vol. 31, No. 3, Access to Higher Education 1985-95: An Extraordinary Decade (Sep., 1996), pp. 289-310 (22 pages)

LETA, May 26 2010, LETA News agency, http://www.leta.lv (accessed 26/05/2010)Mizikaci, F. (2007). Demography: Risks and Opportunities for European Higher Education.

From Here to There: Mileposts of European Higher Education, Baumbgartl, B.Mizikaci, F., Owen D. (eds.). Navreme publications, Vol7a, March 2007, pp 71-85 (available at www.navreme.net)

Moody’s International Public Finance (2009). Global Recession and Universities: Funding Strains to Keep Up with Rising Demand, Special Comment on Higher Education, June 2009.Available at http://www.universityworldnews.com/filemgmt/visit.php?lid=45 (ac-cessed 20/03/2010)A view of Lithuania 2001-2008

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Appendix

Figure A1. Observed(1998-2010)andprojected(2011-2020)age-yearspecificenrolmentratios in Latvia – SER scenario


Figure A2. Observed(1998-2010)andprojected(2011-2100)age-yearspecificenrolmentratios in Latvia – GET scenario


1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

45

35

40

0

30

25

20

15

10

5

17

181920

2122

232425262728

29-3040 plus


1998

% o

f age

gro

up

2001

2004

2007

2010

2013

2016

2019

2022

2025

2028

2031

2034

2037

2040

2043

2046

2049

2052

2055

2058

2061

2064

2067

2070

17

45

40

35

30

25

20

15

10

5

0

18

192021

22

2324

2526272829-39

40 plus

2073

2076

2079

2082

2085

2088

2091

2094

2097

2100

21

Figure A3. Observed(1998-2010)andprojected(2011-2020)age-yearspecificenrolmentratios in Latvia – CRI scenario


30

25

20

15

10

5

0

1998 2000 2002 20062004 2008 2010 2012 2014 2016

17-24

25-28

29 plus

2018 2020


23

The impact of EU Cohesion policy on environmentalsector sustainability in the Baltic states

Sirje Pädam, Üllas Ehrlich, Koidu Tenno1

Abstract

This article analyses investment from European Union cohesion policy funds into the Es-tonian, Latvian, and Lithuanian environmental sectors during the budget period 2007-2013. Total investment from these funds in Estonia, Latvia, and Lithuania during that period will be about 14.7 billion euros, of which about 18 percent covers the environmental sector.

The purpose is to analyse whether allocation of expenditure to the environment is sustainable. Intheiranalysistheauthorsapplysustainabilitycriteriabasedonthecost-benefitruleandtheEnvironmentalPerformanceIndex(EPI).ThemainfindingisthattheBalticStatesallocateleastenvironmentalfundstothosefieldsfoundtobemostrelevanttosustainability.

Keywords: environmental investment, EU funding, sustainabilityJEL classification: H59; Q20; Q28; Q58

1. Introduction

Vincent and his co-authors (2002) note that despite strong reasons for analysing public expen-ditureandtheenvironment,onlylimitedliteratureisavailablewithinthisfield.Sofar,mostanalyses concerning public expenditure on the environment have been undertaken by the WorldBankandtheOECD.Thispaperaimstofillthegapandoffersanovelperspectiveintothe study of allocation of public expenditure to the environment by comparing EU cohesion policy fund allocation to the environment in three countries of similar size and corresponding economic prerequisites.

The analysis concerns the structure of EU cohesion policy funding for the environment in Estonia, Latvia, and Lithuania during the period 2007-2013. Since all countries eligible for funding are subject to the same regulations, it is expected that funding choices will be simi-lar.However,countryspecifictimeschedulesforfulfillingEUdirectivesagreedonduringmembership negotiations can be a source of differences. The overall purpose of the analysis is to assess whether budgetary allocation to the environment according to funding plans sup-ports sustainability of the environmental sector. Funding plans, the outcome of negotiations

1 Tallinn School of Economics and Business Administration, Tallinn University of Technology, Akademia tee 3, 12618 Tallinn, Estonia, corresponding author Sirje Pädam, e-mail: [email protected]: this article was written with the support of the Estonian Ministry of Education and research founda-tion project No 0142697As05.

The impact of EU Cohesion policy on environmental sector sustainability in the Baltic states

24

betweeneachbeneficiarycountrygovernmentandtheEUCommission,aredocumentedinNational Strategic Reference Frameworks 2007-2013 and Operational Programmes.2 The Operational Programmes for Estonia, Latvia, and Lithuania represent the primary source of data of this paper.

Webeginbydescribingthetheoreticalframeworkfordefininganefficientandenvironmen-tally sustainable resource allocation. Based on the theoretical framework, we then present an outline for step-wise assessment of sustainability of budgetary allocation to the environ-mental sector. In the following section we present the outcome of cohesion policy fund al-location in the three Baltic States. After that we carry out step-wise assessment and, based on the results, we classify spending priorities according to their relevance to sustainability. The conclusions are presented in the last section.

2. Theoretical framework

Environmental regulations and public expenditure directed to the environment are generally justifiedbyefficiencyreasons.Thisisbecauseunregulatedmarketspaytoolittleattentionto environmental protection, i.e. environmental quality. Supply of environmental goods may beinsufficientsincetheyarepublicgoods,whileoversupplyofactivitiesthatgiverisetonegative externalities can also occur. The role of government expense on the environment is thus to redirect tax income to provision of public goods and to tax activities that give rise to negativeexternalities.Tosomeextent,environmentalprotectioncanbeselffinancingiftaxesand charges paid by polluters are directed to rehabilitation and pollution control.

In this paper we deal with supra-national funding where Member State payments are re-allocatedamongEUcountries.For thisreason, theconceptoffiscalfederalismcanbeap-plied to allocation of public expenditure. Fiscal federalism addresses the problem of vertical allocationofeconomicresponsibilitiesbylevelofgovernment.Efficientallocationassignstheresponsibilitytotheterritorialauthoritywherebeneficiariescorrespondtothatoftaxpay-ers(seePitlik,2007).Ifthebenefitsofpublicgoodsspillovertoaneighbouringterritoryorcountry, this gives reason to centralize responsibility. Fiscal federalism would thus predict that EU funding to the environmental sector is devoted to environmental issues with cross bordercharacteristics.Inaddition,efficiencyreasonswouldmotivatehigherlevelsoffund-ingwhenneighbouringcountriesbenefitfromimprovements.Pitlik(2007)findsthatalmosthalfthefinancialresourcesoftheEUbudgetareallocatedtospendingcategoriesinwhichEUresponsibilitiesarequestionablefromtheviewpointoffiscalfederalism.Sinceoneoftheintentions of cohesion funding is to reduce disparities among Member States, regions, and individuals³,itislikelythattheconceptoffiscalfederalismisnotapplicableforourpurpose.

Our main focus of environmental spending involves sustainability. Analogous to sustain-able development, sustainability represents resource use that meets human needs while pre-serving the environment so that needs can be met for both present and future generations. The literature suggests a close relationship between efficiency and sustainability (see e.g.

2 See list of references.³ See COM 2008/301 (2008).


25

Pädam, 2003). Efficiency implies resource allocation that considers peoples’ preferencesand accounts for resource constraints. By allowing for reallocation of resources in case hu-manneedsarenotmetandbyadoptingadynamicperspective,efficiencywilloverlapwithsustainability. According to the interpretation by Stavins et al. (2003), sustainability can be understoodasdynamicefficiencyalongafeasibleconsumptionpath.Sustainabilityentailsnon-wastefulness, implying that the choice of a consumption path is such that the economy is on the Pareto frontier. Following Stavins et al.’s application of a Ramsey type of presentation, welfare, W, of such a path can be evaluated over time as:

(1)

where U denotes the utility function which depends on consumption, C, including both direct consumption and enjoyment of non-market goods and services. Time is denoted by τ and t (τ, t≥ 0)andthetimehorizonistakentobeinfinite.Theutilitydiscountrateisdenotedbyr. Since C contains two types of goods, the argument of the utility function can be rewritten as:

(2)

where x(τ) denotesmarket goods and z(τ) denotes non-market goods, including environ-mental goods and services. In order to be sustainable, current decision making must consider the perspective of inter-temporal public goods and inter-temporal externalities. Securing fu-ture supply of environmental goods and services implies production of inter-temporal public goods, which need to be provided so as to include the preferences of future generations. Stavins et al. formulate a condition of intergenerational equity requiring non-decreasing wel-fare:

(3)

The requirement that the stream of welfare does not decline over time implies that future generations will not be worse off. Although constant consumption at no more than subsis-tencelevelcouldinprinciplemeetthedefinitionofsustainability,Stavinset al. (2003) argue thatthisdefinitionwouldnotbeacceptedasmeetingreasonablesocialgoals.Forevaluatingsustainability they propose a decision rule similar to the Kaldor-Hicks criterion, i.e. that those who are made better off by a policy in theory can fully compensate those who are made worse off. A policy that fails the Kaldor-Hicks test cannot pass the stricter Pareto test. In a dynamic context, intergenerational transfers could be applied to achieve non-declining welfare. This isthejustificationfortheirproposaltousedynamicefficiencyasacriteriontofindpoliciesthat are potentially sustainable.

Although intuitively appealing, the approach of Stavins et al. (2003) disregards two central issues: one is the implicit assumption they make about natural capital and the other is the preferences of future generations.

The implicit assumption that they make about natural capital is that natural environments and ecosystems can be represented by equations that are convex sets and that are at least twice differentiable. However, this need not be the case. The reason is that regeneration paths


ττ τ deCUtWt

tr∫∞

−−≡ )())(()( )

))(),(( ττ zxfC = )),

≥ 0dW(t) dt

26

of natural environments and ecosystems tend to exhibit nonlinear dose-response relations, implying that marginal changes in anthropogenic pressure may result in irreversible effects (see Dasgupta and Mäler 2004). Therefore no guarantee exists that equation (3) is non-nega-tiveorthattheinequalitycanbedefinedinameaningfulway.Inananalysisofpolicyreformsin imperfect economies, Arrow et al. (2004) show that social welfare might or might not be sustained between two periods. Reasons why an imperfect economy is incapable of sustain-ing welfare over time include e.g. scarcity of resources and limited substitution possibilities among capital assets. At the same time, Arrow et al.(2004)showthatthegeneralcost-benefitrule holds for guiding sustainable investment decisions in an imperfect economy. But, in or-dertocertifythatthecost-benefitruleproducescorrectestimates,itwillbecomenecessarytoderive proper accounting prices, which can to a large degree differ from market prices (ibid). In theabsenceofproperaccountingprices, theneedarises tofindotherways toconsiderscarcity and the need for preservation of key natural resources.

Finding information about proper accounting prices is not only hindered by lack of know ledgeaboutnon-lineardoseresponserelationsofnaturalenvironments.Anotherdifficultyindeterminingsustainabledevelopmentoveralongperiodorevenmoresooveraninfinitetimespan is lack of information about the preferences of future generations. Current decisions that affect sustainable development would need to take into account estimates of willingness to pay by unborn persons in the distant future. Taking a closer look at decision making, we can see that people do not tend to give up decision making in those cases where their deci-sions tend to have an impact on future generations. In several cases people even include the welfare of their children or grandchildren in their decisions. Monchareva and Gudas 2009 report that a large portion of respondents declare that improving the water quality in theNevezisriverbasinisimportant“forchildrenandforfuturegenerations’wealth”.Thisimplies that current generations have the capacity to represent future generations. Assuming that the preferences of current generations contain the requests of future generations on the natural environment implies that willingness to pay estimates based on generations now alive can be approximated as representative of the preferences of future generations.

However,wecannotexpecttofindthewholeanswerfromwillingnesstopayestimatesbasedon generations now alive. The failure of humans to put an accurate value on critical natural assets is due to the inherent complexity of the natural environment. Taking into account that human preferences cannot correctly sense when ecosystems are at risk implies a need to use knowledge of ecological science in order to identify critical environmental assets.

3. Combined approach

Since it may prove impossible to collect proper accounting prices by estimating willingness topay(WTP)fornaturalenvironmentsandecosystems,i.e.theaccountingpricesofz(τ)inequation (2), from generations now alive, the implication is that a need exists for a combined approach to assess the sustainability of environmental spending. In our analysis we will con-siderthecost-benefitruleinthefirststepforassessingsustainabilityandinthesecondstepwe will use ecological knowledge in order to certify that investments will be undertaken in criticalfieldsofz(τ).ForthepurposeofthesecondstepweusetheEnvironmentalPerfor-mance Index (EPI), (see Esty et al. 2008). This index is based on empirical data about the


27

environment in 149 countries and allows cross country comparisons. The index has been developedbyfirstidentifyingspecificenvironmentaltargetsandthenmeasuringthedistancebetween the target and current national achievement (ibid). Although the authors identify several data gaps, EPI is a comprehensive measure based on ecological knowledge.

In terms of our purposes, EPI is no substitute for WTP estimates. Instead we need EPI in order tocomplement the informationof thecost-benefit rule.SinceEPI isavailable forabroader range of environmental issues than WTP estimates, we will use EPI as an indicator for suggesting additional policy implications when WTP estimates are missing. However, EPI cannot assess the range of required investment and cannot measure whether a certain levelofinvestmentpassesthecost-benefitrule.

4. Budget allocation to the environmental sector

Cohesion policy funding included by the Convergence Objective during the programming period 2007-2013 amounts to about 346 billion euros. Among the Baltic States, funding per country is between 3.4 and 6.8 billion euros. Estonia obtains less than Latvia, and Lithuania receives more than the two other Baltic states. The ranking of the contribution to the environ-mental sector shows similar positions between countries. Lithuania devotes most, then Latvia, while Estonia assigns least funds to the environment, see Table 1.

Table 1. Allocation of cohesion policy funding to the environment, in total and per country 2007-2013, euros current prices**

Sources: Operational Programmes, COM 2008/301(2008) annex 1 and Eurostat (2008). Population data for January 2007: Estonia 1,342,409, Latvia 2,281,305, and Lithuania 3,384,879.

*Community wide covers Member States and regions falling under the convergence objective covering 35 percent of the Union’s population.**Allamountsexpressedincurrentprices.Toaccommodateinflationaryexpectationsduring2007–2013,EUcountriesagreed toadjustfinancial frameworkceilings(expressed in2004prices)byusingayearly2percentpricedeflatorbetween 2004 and 2013.

The primary reason why funding differs between countries is due to country size. Dividing fundingbypopulationputsthesefiguresintoanotherperspective.Thepercapitaallocationof cohesion policy funding to the environment is highest in Estonia and lowest in Lithuania. In comparison to the community wide allocation of cohesion funding that falls under the convergence objective, all three Baltic states devote more to the environment than is directed by cohesion funding on average.

Priority theme Estonia Latvia Lithuania Community Wide*Euro, millionEnvironment 781.3 792.7 1,053.4 46,735.9Total 3,403.5 4,530.4 6,775.5 346,150.8Euro, per capitaEnvironment 582 347 311 270Total 2,535 1,986 2,002 1,997Percent Environment 23.0 17.5 15.5 13.5Total 100.0 100.0 100.0 100.0


28

Thedefinitionofcommunityfundingdevotedtotheenvironmentalsectorincludes12outofa total of 86 priority themes. The chosen priority themes include all but one theme of the cat-egory“Environmentalprotectionandriskprevention”andtwoprioritythemesof“Tourism”:seeEU(2006)foracompletelistofprioritythemes.Ourdefinitionoftheenvironmentalsec-toriscloselyconnectedtofieldscommonlyincludedinenvironmentalprotectionexpenditureofthegeneralgovernmentbudget.Thefieldsusedingeneralgovernmentexpenditureincludewaste management, waste water management, pollution abatement, protection of biodiversity and landscape, and R&D in environment protection.

Expendituretoreducecontributiontoclimatechangeisnotexplicitlyincludedinourdefini-tion other than forming part of pollution abatement. One reason is the choice to follow the fieldsingeneralgovernmentexpenditure.Anotherreasonfornotincludingclimatechangeisthat the Baltic states have different starting points depending on major differences in energy supplybetweencountries.Leavingout investment inenergyefficiency, renewableenergy,and environmentally friendly transportation thus allows for a more equivalent base when making cross country comparisons between the Baltic states. In addition, a comparison of impacts of EU cohesion funding on climate change has been made elsewhere (see CEE Bank-watch Network 2007). Table 2 shows allocation of funding by priority theme of the three Bal-tic states and a comparison with community wide allocation for Member States and regions falling under the Convergence Objective.

Table 2. Cohesion policy funding for the environment, per priority theme 2007-2013, euros per capita current prices** and percent

Source: Authors’ calculations based on Operational Programmes, COM 2008/301(2008) annex 1 and Eurostat (2008). *Community wide covers Member States and regions falling under the convergence objective covering 35 percent of the Union’s population.**Allamountsexpressedincurrentprices.Toaccommodateinflationaryexpectationsduring2007–2013,EUcountriesagreed toadjustfinancial frameworkceilings(expressed in2004prices)byusingayearly2percentpricedeflatorbetween 2004 and 2013.

Priority theme Estonia Latvia Lithuania Community wide*

Management of household and industrial waste 52 8.9% 57 16.4% 82 26.5% 36 13.4%Management and distribution of water (drinking water)

152 26.1% 123 35.5% 61 13.0% 47 17.3%

Water treatment (waste water) 152 26.1% 123 35.5% 41 19.6% 81 29.9%Air quality 10 1.7% 0 0.0% 51 16.3% 6 2.2%Integrated prevention and pollution control 0 0.0% 0 0.0% 0 0.0% 4 1.6%Mitigation and adaptation to climate change 0 0.0% 0 0.0% 0 0.0% 2 0.7%Rehabilitation of industrial sites and contaminated land

103 17.7% 21 6.2% 4 1.4% 20 7.4%

Promotion of biodiversity and nature protection (including Natura 2000)

16 2.7% 11 3.2% 26 8.3% 16 5.8%

Risk prevention (including drafting and implementing plans and measures to prevent and manage natural and technological risks)

29 5.0% 11 3.2% 0 0.0% 34 12.6%

Other measures to preserve the environment and prevent risks

50 8.6% 0 23 7.5% 10 3.6%

Promotion of natural assets 9 1.6% 0 0.0% 23 7.5% 7 2.5%Protection and development of natural heritage 9 1.6% 0 0.0% 0 0.0% 8 3.0%Environmental sector, total 582 100.0% 347 100.0% 311 100.0% 270 100.0%


29

Not all priority themes have been covered by the Baltic states. It is interesting to note that no Balticstatewillinvestintheprioritythemesof“IntegratedPreventionandPollutionControl”or“MitigationandAdaptationtoClimateChange”.Moreover,communitywideinvestmentin these two priority themes is low. Estonia is the only Baltic state to allocate funds to “Pro-tectionandDevelopmentofNaturalHeritage”.Theotherprioritythemesarecoveredbyatleast two Baltic states. In total, Estonia’s funding covers 10 priority themes, Latvia’s 6, and Lithuania’s 8.

All Baltic states prioritise drinking water distribution and waste water treatment. These two priority themes are top priorities in Estonia and Latvia. Lithuania puts top priority on waste management, while drinking water and waste water treatment come at numbers two and four, respectively. Air quality is the third priority for Lithuania, while Latvia’s third is waste man-agement. Estonia’s third priority is rehabilitation of contaminated land. Ranking of priority themesbyexpenditureisrelativelysimilarinEstoniaandLatviaforcommonfields,whileLithuania shows another ranking of priorities in that it includes a relatively large share of promotion of biodiversity and natural assets. Community wide priorities rank waste water treatment as top priority, followed by drinking water supply, and waste management.

Notwithstanding comparable economic prerequisites and similar country size, funding plans for Estonia, Latvia, and Lithuania reveal larger differences than were expected. One reason for greater focus on drinking water in Estonia and Latvia may be that that Estonia and Latvia weregrantedtransitionalperiodsforfulfillingthedirectiveondrinkingwaterquality,whileLithuaniawasexpectedtofulfiltherequirementsonaccession.Inaddition,Estonia’sfund-ing plans cover a larger number of priority themes than Latvia’s and Lithuania’s and shows larger per capita spending on the environment. These differences may be due to the fact that Estonia’sproductionofelectricitygivesrisetosignificantpollutionandthatenvironmentalprotection was a major issue during the struggle to regain independence. Latvia has chosen fewer priority themes than its Baltic neighbours, but will spend more per capita than Lithu-ania. In Lithuania, biodiversity and natural assets receive a larger share of funding than in the other Baltic States.

5. Assessment of sustainability

The observations above raise questions about whether more investment into the environmen-tal sector is better from the viewpoint of sustainability and how the various priority themes add to sustainable development. Based on our initial discussion, sustainability can be as-sessedby thecost-benefit rule.However, sincehumanpreferencescannotcorrectly sensewhen ecosystems are at risk, WTP estimates might not produce proper accounting prices. Therefore, we will need to assess sustainability in two steps.

5.1. Cost-benefit rule

Applyingefficiencymotivationstospendingpriorities,marketfailurecanmotivateallprior-ity themes that were included in the environmental sector. Several priority themes deal with alleviating negative externalities including waste management, waste water treatment, and


30

pollution control. Other priority themes can be motivated by reasons of provision of public goods, including air quality, rehabilitation of contaminated land, and promotion of natural as-sets.Drinkingwaterinfrastructureisnotapublicgood,butitsprovisioncanbeclassifiedasmarket failure since the supply of drinking water infrastructure is characterised by increasing returns to scale.

Existenceofmarketfailureisnotsufficienttoconcludethatacertainprioritythemeneedsfundingforreasonsofefficiency.Inaddition,thecost-benefitrulerequiresthattotalbenefitsexceed total costs, i.e. that willingness to pay (WTP) for the services or goods in question covers costs. Unfortunately, we know very little about whether willingness to pay covers the costs associated with the priority themes. However, some evidence exists for four priority themes.

5.1.1. Waste management and sewerage services

Bluffstone and De Shazo (2003) report estimates of willingness to pay for two priority themes in Lithuania. They estimated the cost of implementing EU directives on waste management and urban waste water treatment and conducted contingent valuation studies among Lithu-anian households in Ukmerge municipality 40 kilometres north of Vilnius. The population is approximately 34,000 and the average monthly household income is close to the national median (see Bluffstone and De Shazo, 2003).

Ininterviewswithhouseholds,thebenefitsofimprovedlandfillconstructionandclosureofoldlandfillsweredescribedintermsofavoidingpollutiontosurfaceandgroundwaterandthatafterclosureoldlandfillswouldbesealedandreplantedtoavoidfuturecontamination.Respondents who indicated they had no access to the sewerage network were surveyed for theirWTP to be connected to themunicipal sewerage system.The benefits ofmunicipalsewerage services were described in terms of there being no need to service their private septic system or pit toilet and no smell once connected to the municipal system. The authors found that at least 50 percent of respondents would be willing to pay 0.62 euros (2.73 litas) moreperpersonandyearforlandfillupgradeandthathalfofrespondentswerewillingtopay an additional 0.51 euros (2.24 litas) per person and per year for sewerage services. The average household size in Ukmerge is 2.67, thus producing household WTP of 1.7 and 1.4 euros respectively.

Assuming that the households studied are representative of Lithuania, the authors estimated that national WTP covers between 80-90 percent of the costs of improving waste manage-ment practices, but that WTP for sewerage services covers only 10 percent of the costs (ibid). Thisimpliesthatneitherofthedirectivesproducesbenefitslargeenoughtocovercosts.How-ever,onelimitationofthebenefitestimationofsewerageservicesisthatbenefitsfromim-provedenvironmentalconditionsaremissing.Theseinclude,forexample,benefitsthatarisefromimprovedwaterqualityinlocalsurfacewaterbodies,enhancedfisheries,andimprovedrecreation opportunities. Since 1.4 euros per household covers only 10 percent of costs, the improved environmental conditions of water bodies resulting from the urban waste water treatment directive must cover at least the remaining 90 percent of the 14 euros (i.e. 12.6), in ordertopassthecost-benefitrule.


31

5.1.2. Water quality

In a recent article, Monarcheva and Gudas (2009) review three contingent valuation studies that have presented monetary WTP estimates for improving the water status in the river ba-sins of the Nevezis (Lithuania), the Ludza (Latvia), and the Valgejogi (Estonia). The Lithu-anian and Latvian studies measured the WTP for improving water quality from poor to good, while the purpose of the Estonian study was to estimate the value of restoration of salmon and otherrarefishspeciesintheValgejogiRiver.Thesestudiesdifferincertainrespects.Firstly,the Lithuanian and Latvian studies focus on water quality and the Estonian on restoration offishpopulations.Secondly,theauthorsmentionasignificantsocio-economicdifferencebetween the Latvian study and the other two, as the Latvian study area has low population density and low income levels. Since WTP estimates are generally strongly correlated to income, it is reasonable to expect that the Latvian WTP is lower than the Lithuanian. The results, expressed in annual WTP in euros per household, are reported in the table below. The values in brackets represent estimates when zero bidders are included.

Table 3. Willingness to pay (WTP) for improving water quality of river basins in the Baltic states, euro per year

In order to use the WTP for water quality estimates we would like to know whether imple-mentation of EU directives on urban waste water management will result in improvements that have been valued by the Estonian, Latvian, and Lithuanian studies. The Estonian esti-mateconcerningrestorationoffishstocksseemslesssuitableforourpurpose.TheLatvianand Lithuanian studies seem to be more in line with expected impacts from improved sewage treatment. Including zero bidders, the Latvian and Lithuanian estimates produce a span of WTP for water quality improvements ranging from 6.2 to 13.3 euros annually per household. Assuming that the Latvian and Lithuanian WTP estimates approximately relate to the water qualitybenefitsoftheEUdirective,thissuggeststhatbenefitsmightnotbesufficienttocoverthe remaining 90 percent of the costs of about 12.6 euros.

5.1.3. Drinking water

Experience from Poland implies that public willingness to pay for municipal services is higher for drinking water than for waste water services: see Stanek (2002). This seems logi-cal based on the fact that people pay relatively more for safe drinking water, such as bottled water. However, a high WTP for drinking water does not seem to be the case for the Ukmerge municipality. One explanation may be that the WTP for safe drinking water only concerns a limited quantity of the water consumption of an average household. In the background documentation of the Ukmerge study, DEPA and DANCEE (2001) report the WTP for water

Environmental good WTP per year per household, euros

RestorationofsalmonandotherrarefishspeciesinValgejogiriver(Estonia)

22.8 (22.8)

Improving the water quality of Lake Ludzes and the upper part of the river Ludza river basin (Latvia)

13.7 (6.2)

Water quality improvement of the Nevezis River basin (Lithuania) 20.5 (13.3)


Source: Monarcheva and Gudas (2009)

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supply. According to DEPA and DANCEE (2001), the quality of tap water distributed to householdsinUkmergemunicipalityischeckedregularly,butduetoinsufficientwaterpipemaintenance, households from time to time receive tap water with an orange/red colour or anodour.RespondentsinUkmergewereaskedtovaluethebenefitofupgradingthewatersupply pipes to ensure that the water supply system would be safe and so that no colour or odour would be present. The WTP was estimated to be 1.44 litas per person, per year, which corresponds to approximately 74,880 litas per year for the whole municipality. The estimated annual cost of upgrading the water supply pipe in Ukmerge municipality was estimated at ap-proximately10millionlitas,suggestingthatbenefitscoverlessthan1percentofinvestment.

5.1.4. Promotion of biodiversity

Ehrlich et al. (2008) compared the costs andbenefits of biodiversity enhancement by ex-panding the area covered by semi-natural plant communities in Estonia. Semi-natural plant communities, such asmeadows,were developed by scythe, axe, fire, and grazing.Theselandscapes can persist only with support from human activity, such as mowing, grazing, and brush cutting. In 2007, semi-natural plant communities covered approximately 10,000 hect-ares in Estonia and the area is declining. Since these semi-natural plant communities are a prerequisite for richness in biodiversity and for migrating birds, the decline of traditional farming activities has put biodiversity under threat.

Ehrlich et al. (2008) estimated that annual WTP was 265 euros per hectare of semi-natural plant communities. This amount was derived from the annual WTP estimate of 11.8 euros per person of the working age population. Based on an inventory covering all 31 protected areas in Estonia, the costs were collected for extending preservation of semi-natural plant communities to all Natura 2000 areas. This inventory was a base for Estonia’s funding plan for the priority theme promotion of biodiversity and nature protection. The present value of costs for extending the preservation areas to 19,334 hectares was estimated at 56.3 million euros. The cost estimate includes both running costs and investment costs during a 30 year periodusingadiscountrateof5percent.Thepresentvalueofbenefitswasfoundtobe89.0million euros. The results indicated that willingness to pay for biodiversity enhancement exceeded costs by 58 percent.

5.1.5. Benefit transfer

Thecost-benefitrulecanonlybeappliedtofourprioritythemes,andthisscatteredevidencegives point estimates for Lithuania in three out of four cases and in one case for Estonia. Ben-efittransferfromonecountrytoanotherisarelativelycommonpracticeinliteratureandforpolicy purposes. However, differences in socio-economic characteristics and in the physical characteristicsofstudysitesinfluenceWTP.Generally,incomeisthemostimportantvariableaffecting WTP estimates.

The authors of the Lithuanian studies (see DEPA and DANCEE, 2001 and Bluffsone and De Shazo, 2003) assume that their results can be transferred to Lithuania as a whole. This


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is based on the fact that the socio-economic characteristics of Ukmerge are assessed as rep-resentative of the whole country. The Estonian study is based on a representative sample of the working age population (see Ehrlich et al. 2008). There are some differences in GDP per capita between the Baltic States, but from an EU perspective the income levels are similar. In addition, EU directives have imposed comparable requirements on the Baltic States.

Assuming that it is possible to transfer the above results between the Baltic states implies that too many funds will be devoted to improving drinking water supply. Waste manage-ment funding probably also receives more funds than desirable. Connection to the municipal seweragesystemandupgradedwastewatertreatmentcanonlybemotivatedifthebenefitsofimprovedwaterqualityareaddedtothebenefitestimate.Thescatteredevidencefurthersuggests that promotion of biodiversity receives too little funding. The results thus imply that fromanefficiencypointofviewthefundingplanswillobligetheBalticstatestoinvestmorethan is socially desirable in drinking water and waste management. The implication is thus thatsupporttodrinkingwaterandwastemanagementshouldbereduced,whilefinancingofbiodiversity should be increased.

5.1.6. Cross border benefits

Priortoarrivingatconclusionsconcerningthefirststepoftheassessment,itwillbeimpor-tanttoassesspotentialcrossborderbenefits.Weexpectthatmoreexpenditureisallocatedtoprioritythemesthatgiverisetocrossborderbenefitsthancanbemotivatedbynationalbenefits.

The priority themes of the environmental sector that can motivate costs exceeding national benefitsarethosethathavesignificantcrossborderimpacts.Potentialprioritythemesincludepollution control in those cases when air and water pollutants spread on a regional scale. Reductionofenvironmentalriskcouldhavecrossborderbenefitsifenvironmentaldamagespreads across national borders. Promotion of biodiversity, natural assets, and natural heri-tagemightalsohavecrossborderbenefitsifcitizensinothercountriesexpressusevalueornon-use value for preservation.

Probablythemostimportantcrossborderbenefitsarethosethatconcernthewaterqualityofthe Baltic Sea. In the mid 1990s an extensive inter-disciplinary study on the state of the Baltic Sea was carried out by Turner et al. (1999). The authors simulated a 50 percent nitrogen and phosphorus reduction scenario. According to Turner et al. this corresponds approximately to nutrient levels of the Baltic Sea in the 1960s before its drastic deterioration. Cost effective policies for reducing nitrogen levels were found to include increased waste water treatment capacity at sewage treatment plants, reduction of use of nitrogen fertilisers, and construction of wetlands. Sewage treatment was proposed as a relatively low cost reduction option for reductionofphosphorous.Ontheotherhand,benefitsofwastemanagementandofimprove-ment of drinking water are geographically limited and high funding levels cannot be moti-vatedbycrossborderbenefits. Thecostsofnutrientreductionswerecomparedtothebenefits.TwoWTPsurveyswerecar-ried out: one in Poland and the other in Sweden, asking the adult population in each country


34

for their willingness to pay for a 20 year action plan to reduce eutrophication in the Baltic Sea.Theactionplanwouldbefinancedbyintroductionofanextraenvironmentaltax.Thewillingness to pay estimates were transferred to the other countries around the Baltic Sea by adjusting WTP estimates to the levels of GDP per capita. The Polish values were transferred to the formerly planned economies and the Swedish values were transferred to the other countries: see Turner et al. (1999).

Inordertoachieveabetterfittocurrentcircumstances,WTPestimatesforimprovingthestatus of the Baltic Sea have been updated and new estimates have been derived by using meta-regression analysis based on a large number of willingness to pay studies for improved water quality: see Huhtala et al. (2009). The authors found an average WTP of 60 euros per personandperyear.ThiswasthenconvertedtocountryspecificestimatesbyusingcountryspecificdataonGDPpercapita.TheresultsareshowninTable4.Thepopulationfiguresrepresent an estimate of the adult population in the Baltic Sea drainage basin of each country.

Table 4. DistributionofbenefitsbetweenBalticSeacountriesbasedonmeta-regressionre-sults,benefitsineuros2007

Source: Huhtala et al. (2009)

Clearly, the WTP estimates for sea water quality in the Baltic States are higher than the WTP estimates for water quality in river basin areas reported in Table 3. This is in line with the findingsofHuhtalaet al.(2009)whoreportthatthetypeofwaterbodyisinfluentialindeter-mining willingness to pay values. If the affected water body is a sea area, willingness to pay is on average 31–42 euros higher than for other water bodies. Although improved waste water treatment represents only one of the measures for achieving better Baltic Sea water quality, theWTPestimatesinthetablesuggestthatthebenefitsaresubstantialforallcountriesthatborder the Baltic Sea.

5.2. Environmental Performance Index

Theefficiencycriterionintermsofthecost-benefitrulecarriesinformationaboutthedesir-abilityofinvestmentinasustainabilityperspective.However,theproblemoffindingproperaccounting prices necessitates collection of inputs from other sources about the state of the environment.Forthisreasonandsinceavailableevidenceofthecost-benefitruleisrather

Country Average annual WTP per person

Population (in millions)

Benefits per year (million euros)

Percentage of total benefits

Estonia 45.2 1.05 47 1.8%Latvia 38.8 1.78 69 2.7%Lithuania 40 2.42 97 3.8%Denmark 71 3.58 254 9.9%Finland 68 3.86 262 10.2%Germany 66.2 2.45 162 6.3%Poland 36.6 25.85 946 36.9%Russia 33.5 7.00 235 9.2%Sweden 72.6 6.78 492 19.2%Total 54.77 2 564 100.0%


35

narrow, we have chosen an empirical source that allows cross country comparison about environmental status.

The Environmental Performance Index (EPI) gives input by assessing current national achie-vement towards environmental targets (see Esty, et al. 2008). The two overarching environ-mental objectives of EPI include: reducing environmental stress to human health (i.e. envi-ronmental health) and promoting ecosystem vitality and sound natural resource management. These objectives and the overall ranking of the eight Eastern European countries that joined the EU at the same time as Estonia, Latvia, and Lithuania plus Switzerland is shown in the figurebelow.ThereasonforincludingSwitzerlandisthatthiswasthecountrywiththehigh-est EPI in 2008.

Latvia, with an index of 89, scores the highest value of the index among the East European countries that joined the EU together with the Baltic states. Lithuania and Estonia have 86 and 85 as index values, placing them top after Latvia and Slovenia. Based on Figure 1, it is also possible to conclude that the problems of environmental performance in Eastern Europe involve ecosystem vitality and sound natural resource management rather than environmen-tal stress to human health (i.e. environmental health). This might be taken as an additional indication of over-investment in such priority themes as drinking water supply.

The ecosystem vitality index is further decomposed into four indicators. Figure 2 takes a closer look at this index of the Baltic States. Three of the indicators show the status of threats to ecosystems, such as water and air pollution and climate change, and the fourth indicator

Figure 1. Environmental performance index of countries that became EU members in 2004 plus Switzerland, EPI 2008

Source: Esty et al. (2008)


90

80

70

60

100

0

50

40

30

20

10

Czec

h Re

p.

Pola

nd

Hun

gary

Esto

nia

Slov

akia

Lith

uani

a

Slov

enia

Environmental Performance Index (EPI) Environmental Health Ecosystem Vitality

Maximum, inbex=100

Latv

ia

Awitz

erla

nd

77

92

62

80

94

67

84

98

70

85

98

73

86

99

73

86

95

77

86

98

75

9589

82

9699

92

36

measures the state of ecosystems including aspects such as species protection, forest, agri-cultural,andfisheryre-productivity.TheBalticstatesscorerankslowestinbiodiversityandproductivity of natural resources. Estonia has a low position in climate change depending on large-scale use of oil shale in its energy sector.

Figure 2. Ecosystemvitalityindexdecomposedintofourfields(maximumindex=100),Bal-tic States 2008.

Source: Esty et al. (2008)

The policy implications of EPI are that the Baltic states should pay more attention to biodi-versity(e.g.conservationofhabitats)andproductivityofnaturalresources(e.g.fisheryandcroplandintensity).BothefficiencymotivationsandEPIthussuggestthatmorefundsshouldbe allocated for biodiversity and less for drinking water provision. In addition, EPI proposes thatmoreattentionispaidtoenhancementofnaturalresourceproductivity,i.e.fisheriesandcropland. In terms of priority themes, rehabilitation of industrial lands, promotion of biodi-versity, and promotion of natural assets are put forward by EPI. Although water quality does notstandoutasbeingatrisk,productivityoffisheriesneedsattention,thusindicatingtheimportance of upgrading waste water treatment.

6. Relevance to sustainability

The analysis in the previous section suggests some implications for sustainability of cohesion fund allocation to the environmental sector in the Baltic states in 2007-2013. However, it was not possible to include all priority themes in the analysis because of gaps in knowledge aboutthebenefitsandcostsofseveralprioritythemes.Wastewatertreatmentandpromotionofbiodiversitypassedthecost-benefitrule.Managementofhouseholdandindustrialwastedidnotpassthecriterion,althoughbenefitswerenotfarfromcoveringcosts.Drinkingwatersupply was rejected.


Estonia Latvia Lithuania

Water Quality Air Pollution Biodiversity & productivityof natural resources

Climate Change

62

95959998

79

7173

65

87 89

98

90

80

70

60

100

0

50

40

30

20

10

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EPI was used as a complementary input, and supported the scattered evidence of the cost-benefitrule.Inaddition,EPIsuggestedthatrehabilitationofindustriallands,promotionofbiodiversity, and promotion of natural assets would be important from an ecological point of view. In order to arrive at an overall assessment we will take the analysis one step further by classifyingallprioritythemesunderstudyintofourfields(seematrixinTable5).

Table 5. Classificationofprioritythemes2007-2013

BiodiversityenhancementinEstoniawassupportedbythecost-benefitrule.Inaddition,EPIfurther highlighted the need to promote biodiversity and resource productivity in the Baltic States.Fourprioritythemesareclassifiedasenhancingbiodiversityandresourceproductivityandthesewillbeclassifiedashighlyrelevantforsustainabilityoftheenvironmentalsector.

The theoretical framework emphasized the long run perspective and proposed that sustain-abilityconcernsfuturegenerationsintoaninfinitefuture.Thislongtermperspectivehassofar not been highlighted by the analysis. Since preventive measures allocate funding to future environmentalproblems,thiscategorywillbeclassifiedashighlyrelevanttosustainability.Three priority themes are included among preventive measures: mitigation and adaptation to climate change, risk prevention, and other measures to reduce risks.

Four priority themes aim at reducing pollution. These include waste management, waste water treatment, air quality, and integrated pollution control. According to EPI, the status of water and air pollution is at satisfactory levels in Latvia and Lithuania. At the same time, WTPestimatesforimprovingthewaterqualityoftheBalticSeashowsignificantbenefits.Theleveloffundingofwastemanagementdidnotpassthecost-benefitrule.Theseconsider-ations imply that investment in pollution control can be considered as having medium to high relevance for sustainability.

Theremainingexpenditureisclassifiedasincidentalenvironmentalexpenditure.Thisclas-sificationfollowsVincentet al. (2002) who classify incidental environmental expenditure as expenditure undertaken for non-environmental reasons. Drinking water infrastructure falls underthiscategory.Neitherthecost-benefitrulenorEPIsuggeststhatdrinkingwaterisim-portant from the perspective of sustainability. Incidental environmental expenditure is thus classifiedashavinglowrelevancefromasustainabilityperspective.Table6belowshowsfundingsupportfromEUcohesionfundsaccordingtothefourfieldsdefinedabove.

The table shows that the Baltic States have allocated 10-24 percent of cohesion funds to bio-diversity and resource productivity. Preventive measures receive 3-14 percent of funds. This

Biodiversity and resource productivityRehabilitation of contaminated landBiodiversity and nature protectionPromotion of natural assetsProtection of natural heritage

Pollution controlWaste managementWaste water treatmentAir qualityIntegrated prevention and pollution control

Preventive measuresMitigation and adaptation to climate changeRisk prevention (plans and measures to prevent and manage natural and technological risks)Other measures to preserve the environment and reduce risks

Incidental environmental expenditureManagement and distribution of drinking water


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impliesthatthetwofieldsfoundtohavehighrelevanceforsustainabilityhavebeenallocatedless than half of the cohesion policy funding directed to the environmental sector. Latvia devotesleastfundsforinvestmentinfieldsthatwilladdmosttosustainability(12.6percent).Estonia allocates 37.1 percent and Lithuania 24.6 percent of environmental cohesion funding tothesetwofields.

Funds for reducing pollution were found to have medium to high relevance for sustainability. Pollution control receives more than half of the funds devoted to the environmental sector in Latvia and Lithuania and a little more than one third in Estonia. In per capita terms, funding is on a similar level in the three countries and will receive about 200 euros per capita in each countryduringtheperiod2007-2013.Incidentalenvironmentalexpenditure,thefieldclassi-fiedashavingleastrelevancetosustainability,willreceivebetweenonequarterandonethirdof funding to the environmental sector.

Itisevidentthatprioritythemesclassifiedashavinghighestrelevancetothesustainabilityperspective receive less funding than priority themes found to be of low and medium/high relevance to sustainability. Estonia, with its larger per capita contribution to the environ-ment,alsoshowshigherinvestmentbothinabsolutetermsandinpercentagestofieldshighlyrelevant to sustainability. Lithuania, which ranks lowest according to its per capita funding, showsabetterpositionthanLatviaconcerningallocationtofieldshighlyrelevanttosustain-ability.

Table 6. Cohesionfundingfor theenvironmentalsectorclassifiedbyrelevance tosustain-ability, euros million current prices, euros per capita and percentages 2007-2013

Euro, million Estonia Latvia Lithuania TotalBiodiversity and resource productivity 184.2 75.0 180.7 439.9Preventive measures 105.5 25.2 78.6 209.2Pollution control 287.8 411.0 656.6 1,355.4Incidental environmental expenditure 203.9 281.5 137.4 622.8Total 781.3 792.7 1,053.4 2627.4Euro, per capitaBiodiversity and resource productivity 137 33 53 63Preventive measures 79 11 23 30Pollution control 214 180 194 193Incidental environmental expenditure 152 123 41 89Total 582 347 311 375PercentBiodiversity and resource productivity 23.6% 9.5% 17.2% 16.7%Preventive measures 13.5% 3.2% 7.5% 8.0%Pollution control 36.8% 51.8% 62.3% 51.6%Incidental environmental expenditure 26.1% 35.5% 13.0% 23.7%Total 100.0% 100.0% 100.0% 100.0%


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7. Conclusion

The purpose of this paper is to evaluate sustainability of investment plans of EU cohesion policy funds for the environment in Estonia, Latvia, and Lithuania during the budget period 2007-2013.Theoreticalliteratureshowsthattheefficiencycriterion,i.e.thecost-benefitrule,is applicable to identify sustainable investment. But since natural environments are complex, properaccountingpricesmaybehardtofindwhenrelyingonhumanpreferences.Withthesedifficultiesinmind,weappliedastep-wiseassessmenttoidentifysustainability.Economicefficiencywasconsideredbyusingthecost-benefitrule.InthesecondstepweusedtheEn-vironmental Performance Index (EPI) as a complementary indicator and to identify whether criticalfieldsofinvestmentintheenvironmentalsectorhadbeenleftout.

Useofthecost-benefitrulerequiresinformationonbenefitsandcostsofplannedinvestment.This information was only available for four out of twelve priority themes. Assuming that benefit transfer ispossiblebetween theBaltic states, availableevidence suggests that toomuch funding is devoted to investment in drinking water infrastructure. Neither did manage-mentofhouseholdandindustrialwastepassthecost-benefitrule,thoughbenefitswerenotfar from covering costs. Investment in sewerage services and waste water treatment were notpossibletomotivateunlessbenefitsfromenvironmentalimpactsonwaterbodieswereincluded. Another implication is that investment in biodiversity protection could be extended sincebenefitssignificantlyexceedcosts.

Thecomplementary inputofEPIsupported thescatteredevidenceof thecost-benefitrule.EPI showed that the Baltic States have no serious concerns related to environmental stress to human health, which might be taken as an additional indication that allocation of cohe-sion funds represents over-investment in drinking water infrastructure. The implication of the environmental performance index is that more attention should be paid to biodiversity (e.g.conservationofhabitats)andproductivityofnaturalresources(e.g.fisheryandcroplandintensity).Althoughwaterqualitydidnotstandoutasbeingatrisk,productivityoffisherieswas suggested by EPI to be at a low level, thus indicating the importance of upgrading waste water treatment.

Both steps of our analysis had similar implications, but neither was detailed enough to enable an assessment of all priority themes. In order to obtain an evaluation of all priority themes, weclassifiedthemintofourfields.Thesefieldswerecategorizedaccordingtotheirrelevancetosustainability.ThemainfindingisthattheBalticStatesallocateleastinvestmenttothosefieldsoftheenvironmentalsectorfoundtobemostrelevanttosustainability,i.e.preventivemeasures, and biodiversity and resource productivity.

Investment in drinking water was assessed as too large from the sustainability perspective. Having as an objective to reduce disparities between Member States, distributional consid-erations may have guided funding plans. It is not clear, though, how extensive investment in drinking water infrastructure promotes this purpose.

AnotherfindingisthatthethreeBalticstates,havinglargesimilaritiesconcerningrecenthis-tory,levelofeconomicdevelopment,andnaturalenvironment,showsignificantdifferencesconcerning their priorities. Estonia has the highest per capita contribution to the environ-


40

mentalsectorandalsolargerinvestmentinfieldswiththehighestrelevancetosustainability.Lithuania ranks lowest according to its per capita funding, but shows a better position than Latviaconcerninghighlyrelevantfields.ItispossiblethatEstonia’ssignificantenvironmen-tal problems stemming from oil shale based energy production have made the country more inclined than its Baltic neighbours to invest in the environmental sector and also more ready todirectinvestmentintofieldswithhighrelevancetosustainability.

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43

Credible commitment and cartel: the case of the Hansa merchant in the guild of

late medieval Tallinn

Kaire Põder1

Abstract

This paper contributes to the ongoing debate of institutional research in economics and the methodological debate over the plausibility of using analytic narratives, in social sciences in particular. Using a single historical case we argue that in Tallinn by and large the merchant guild solved a commitment problem in the Hanseatic League and the organisation-institution oftheguildwasmeantforefficientenforcementofinter-citytrade.Weshowthatthisargu-ment holds in the late medieval period by using an extensive form of punishment and sanc-tions game. We also argue that after the breakup of the Hanseatic League, guilds turned into protectionist and rent-seeking cartels.

Keywords: economic history, credible commitment, analytic narratives, reputation mecha-nism, Hanseatic LeagueJEL Classification: C72, D81

1. Introduction

This paper contributes to the ongoing debate about the role of the guilds in the late medieval city-state, and most of all to institutional research using the analytic narrative. First we state that territorialcraftguildsefficientlysolvecoordinationproblemsin theearlydaysof theHanseatic League2 and are thus economic growth-enhancing organizations, partly substitut-ing missing markets. The second argument is that merchant guilds create growth by generat-ing trade through credible commitment to honest trade. In this case a credible threat is created throughthe“reputationmechanism”.Thethirdargument is that in laterperiods–startingfrom the declining era of the Hanseatic League – guilds started to perform as rent seeking organizationsorcartels.Historicalempiricsornarrativesconcentrateononespecificcase–one of the most important city-states in eastern trade: Tallinn (known in history as Reval).

Institutions are rules of the game, writes North (1990). Institutions set the standards, structure society, and limit our freedom. The study of institutions seeks to answer at least two ques-

Credible commitment and cartel: the case of the Hansa merchant

1 Tallinn University of Technology, [email protected]² The word Hansa (hanse, hense) has German roots, originally used in the sense of warrior band, later meaning tribute paid by merchants, sometimes a group of merchants abroad (Dollinger 1970: xix). Here, Hansa indicates the institu-tional arrangement of the inter-city union or federation of cities called the Hanseatic League.

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tions: why institutions are needed, and how institutions are enforced. Our paper investigates governance of the medieval town through the institutional framework. We ask why guilds wereneeded,whom theybenefited, andhow they structured themedievalworld.Neithereconomists nor historians completely agree upon the role of the market in medieval society. Moreover, the question of institutions as substitutes for or complements to markets is still open to debate. We intend to show that institutions can be market-, trade-, and growth- sup-porting, as well as restricting.

Medieval society appreciated the status quo. Appreciation of a static world, including the relevant symbols, social structure, and social norms, can be expected in societies where un-certainty and risks prevail. Fostering the status quo was enforced through the social structure, where materialistic well-being was not an objective, rather a social status-related privilege (Le Goff 2000: 308). However, there is an exception: European economic growth between the tenth and the fourteenth centuries was facilitated by the “commercial revolution of the MiddleAges”–there-emergenceofMediterraneanandEuropeanlong-distancetrade(Lopez1976). This European growth was not a general phenomenon but was rather geographically concentratedinthe“clubs”ofcity-states(inItalianandotherMediterraneancities)andinter-city unions (e.g. the Hanseatic League).

StartingfromtheCliometric“revolution”inthe1950s,economichistoriansbegantoutilizeeconometrics for assessing the functioning of markets in many historical episodes. However, alteringthemethodologytostudycase-specificorcomparativeinstitutionsisrelativelynew.In most literature about medieval Tallinn, the fact of prosperous international trade during the Hanseatic League is largely assumed without much formal testing. However, as Greif (1995) asserts:

[...] the neo-classical approach to the study of institutions through economic history established that contrary to the claims of traditional historians, it is not true that the governance of exchange markets is a very recent phenomenon. Furthermore, by revealing the economic rationale beyond various contrac-tual relations and patterns of ownership it tends to support the Coasian view of non-market institutions as substitutes for the markets (Greif 1995:5).

The New Institutional Economics attempts to explain even more: to show “why institutions that produce poor economic (andpolitical) performance can persist” (North 1993:12). Inmostcases,economicoutcomesdependonefficientinstitutionalchange.Themostintensive-ly studied historical institutional tracks are property rights, and institutions which enabled technological change. In medieval studies, North and Thomas (1973) investigated the spec-tacular economic expansion of the late medieval period. Greif (1995) asserts that many ques-tions which then remained unanswered demanded methodological improvement or change, which was provided by clear concepts of institutions and game theory.

Organizations are non-technologically determined constraints (other than expectations) that impact be-havior by introducing a new player (the organization itself), changing the information available to play-ers, or changing payoffs associated with certain actions. The court, the regulator, the credit cooperative, thecreditbureau,thefirm,andthemerchantgildareexamplesofsuchorganizations(Greif1995:8).

In game theory we are after organizations which are self-enforcing. This makes multiple equilibria games fascinating tools which can be enriched with historical data. The multipli-city and indeterminacy of equilibria in strategic situations indicate that details of the his-


45

torical context are potentially important in the selection of institutions, the implications of a particular institution, and institutional path dependence (Greif 1995:9). In order to construct suchanenrichedgametheoreticmodel, it isvital tocapture thechoice-specificdetailsofthehistoricalsituation.Inidealcases,weneedamicrolevelstudyformodelspecification.Historical institutional studies using microeconomic or game-theoretic tools have a relatively shorthistory. InGreif’s(1989,1993)analysisof“Maghribi traders”,contractualrelationsbetween merchants and their overseas agents in eleventh-century Mediterranean trade are analyzed, to show how to motivate merchants to participate in sanctions when necessary. A created institution can be called a coalition, which made reciprocal information transmission and collective punishment self-enforcing. Similarly, Milgrom et al. (1990) argued that the use of merchant courts in the Champagne Fairs during the twelfth and thirteenth centuries can be analyzed as an institution that created proper incentives for gathering information, honouring agreements, and reporting disputes. All these lowered transaction costs and allowed reliance on markets. There are also other game theoretic studies; for example, Greif (1998) analyses agency relations in twelfth-century Genoa, showing the rationality of creation of inter-clan cooperation and enforcement of external governance institutions called the podestá. Using aninfinitelyrepeatedcompleteinformationgame,Greifet al. (1994) examined the operation of an organization that enabled late medieval rulers to commit to the property rights of alien merchants. This study is of particular interest to us, because it uses the merchant guild as an example of a particular organization that supported a multilateral reputation mechanism. A multilateral reputation mechanism can potentially overcome the commitment problem at the efficientleveloftrade,butonlywhenanorganizationexistswiththeabilitytocoordinatetheresponses of all merchants to abuses against any merchant (Greif 1995:18). Greif (1995:748) also states that the argument concerns merchant guilds and not craft guilds. In the latter, the“commonknowledge”ormonopolizationargument(e.g.HicksonandThompson1991,Gustafsson 1987, Ekerlund and Tollisson 1981) still holds. We may say that the literature provides evidence of growth-enhancing and retarding institutions or organizations.

Our methodology is the analytic narrative. The analytic narrative is a combination of rational choice based game and historical-anthropological or qualitative study. Our narrative com-bines various sources of historical material. Compared to Scandinavian and German mer-chant guilds, some unique documents are available about Tallinn merchant guilds, but no comprehensive study has been undertaken. Thus a synthesis of the narrative is of value in itself. This of course opens us to criticism if the narrative is not well presented. However, we are sure that the case of Tallinn is too interesting to leave aside. And in this study historical narrative is used for explanatory purposes – to show that the guild was a solution to the col-lective action problem. The analytical part of the narrative derives from analysis of choice rules and payoffs of individuals using an extensive form game. The paper proceeds as follows. Section 2 reports the relevant pre-knowledge about the Han-seatic League’s history. Our study covers approximately 100 years, from the foundation of themerchantguildinapproximately1363,untiltheclosingoftheNovgorodofficein1478.Section 3 introduces the problem of credible commitment. Then, in section 4 we propose the model of the agency which enforced unilateral sanctions as a credible threat. Later we discuss the historical context in the case of the Tallinn merchant guild, showing that the guild was the only mediator of trade and that the threat of punishment was accompanied by the guild’s regulations. Finally, we follow the guild’s further development into a rent-seeking institution.


46

The last section concludes the paper by considering the subsequent history of the decline of the Hanseatic League, and proposes a course for further studies including elaboration of a theoretical framework from neighbouring disciplines.

2. Introduction to the narrative: the Hanseatic League

Long distance trade in late medieval Europe was based on exchange of goods through dif-ferent towns or fairs located in geographically or politically favourable places. Yet the gains from trade were insecure not only because of technological constraints (North and Weingast 1989), but also because of many political and institutional constraints: wars, piracy, cheating. The narrative will show that in response to these uncertainties, two possible risk-pegging mechanisms were available: 1) military action or 2) a mechanism for sanctioning shirkers. Which mechanism was more cost-effective? It is argued (Greif et al. 1994:751) that before thefifteenthcentury,defensivetechnologywassuperiortoanoffensiveone.Thus,comparedtomilitaryaction,“diplomatic”actionoreven“tradesanctions”suchasembargoswerecost-effectivemeasures for enforcementofmutualbenefits from trade.Wewill argue that themerchant guild, which enforced a unilateral reputation mechanism, helped to protect trade from shirkers.

In 1189, the Hanseatics – Germans and Gotlanders – signed the oldest known treaty with the Russian Prince Jaroslav, stipulating similar privileges to Russian and German merchants. In 1205, merchants created the Peterhof – a base for traders in Novgorod, which then created the firsttradeorganizationcalledakontor(Dollinger1970).In1229,freetradewasre-confirmedunderthe“GotlandCommunity”(Sartorius1830).Startingfrom1280,Lübeckwascalledthecapud et principiumofallHanseatictowns(Christensen1957:107).Thefirsttradingroutesto Novgorod crossed Tallinn via Lake Ladoga and the rivers Neva and Volga. “Eastward expansion”createdaprofitable trading route for theHanseaticLeagueandTallinnwas atrading establishment for the east-bound trade. In 1230, two hundred German merchants ac-companied by Danes and Swedes settled in Tallinn. Tallinn became a base for operations and assembly-point for German merchants travelling to Novgorod by sea.

Figure 1. Overview of the Hanseatic League’s history and our study (1363-1478)

In Germany, cities emerged through a political process (Greif 1995:21) that led to the estab-lishment of relatively small cities. Hence, the community or organization of the Hansa – or as Greif (1995) states, an inter-city merchant guild – emerged to govern relations between Ger-


47

man merchants. Trade started only after negotiating appropriate safety arrangements (Doll-inger1970).Theorganizationalunitforthiscoordinationabroad–theofficeorkontor – was theconditionalresidenceofHansamerchantsinaparticulartown.Any“commonmerchant”who arrived in a non-Hanseatic town could join the local kontor, which coordinated disputes andfinancialobligations.Hanseaticprivilegeswereconditionaloncitizenshipofthemembertown. The number of active Hanseatic member-towns varied between 55 to 80, but more than 180 towns were somehow related to Hansa trade (Dollinger 1970:88). Active members had to attendannualconferencesordiets(heldinLübeck):theonlyofficialorganizationaltoolforcentralplanning,sincetheHanseaticLeaguehadnoofficialadministrative,military,orfiscalapparatus. From 1356 onwards the regularly held annual Hansetag, the general assembly of Hanseatic towns, was the only controlling organ of the league. Assemblies were mainly held in Lübeck and because of the heavy cost of travel, not all members participated. Delegates from the town councils voted over regulations of the Hansa under a simple majority rule (Dollinger 1970:95), although Lübeck, being always present, played a vital role in Hansa af-fairs.Startingfrom1347,intheHansastatutesthethree“thirds”ofthecitieswerementioned–TallinnwasoneoftheleadingfiguresintheGotland-Livonia“third”(Dollinger1970:95).Several times yearly, local or regional assemblies were also held: these sent their deputies to thegeneraldietanddecided“morelocalaffairs”:

It [the nature of the Hanseatic League] was neither a society, nor a college, nor a corporate body, but a permanent federation of towns owing allegiance to various princes, having no common institution

– even the Hanseatic diet was not admitted as such – and consequently not responsible for the acts or undertakings of any of its members (Dollinger 1970:106-107).

Thusthequestionarises–howcouldthisloose“organization”expandandcreategrowthformany centuries? Greif (1995) believes that this could have only been accomplished through mutuallybeneficial cooperation.Merchantguilds emergedand supported tradeexpansionand market integration “[…] and their function was to ensure the coordination and internal enforcementrequiredtomakethethreatofcollectiveactioncredible”(Greif1995:19).Wasitreallyso?AccordingtoDollinger(1970),first,inthecaseofconflicts,thematterhadtobediscussed in the circle of neighbouring towns (any participation by the territorial ruler in this mediation had to be avoided). Second, if this was unsuccessful, the matter was brought up intheHansadiet,whichmadethefinaldecision–inthemostseverecases,exclusionofthetown from commercial privileges, never military action. In some cases, exclusion could ap-ply to individuals, but then sentence was pronounced by the town where the merchant was a burger or by the kontor–includingconfiscationofgoods(inthecaseofsmuggling),orexclu-sionfromtherightsofa“commonmerchant”.Third,onlyinextremecasesweremoreseveresanctions used such as suspension of trade by embargo or war. An embargo or a war is clearly damaging for all sides, making enforcement in a loose organization even more complicated. The ultimate sanction – war – was used only against piracy, not for economic domination, and even then a great number of towns tried to evade the burden because of heavy military expenses(Dollinger1970:112).Thusthe“optimal”institutionoftheHansawasneitherablenor willing to provide the public good with military action for protection but provided the public good with economic growth through trade.


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3. Setting up the problem: credible commitment

As Bardhan (2005) points out, literature on the economic analysis of social and political in-stitutions has focused mainly on the role of those institutions as protectors of property rights. A more neglected role of institutions is to correct coordination failures or commitment prob-lems that sometimes plague the most basic type of economic interaction. In our study, the merchants’welfarewasdependentonefficienttrade.“Internationalprices”signalledrelativescarcityandgaveinformationaboutefficientexchange,buthugeriskswereinvolvedintrade.Formal business organization of the merchants was practically non-existent – a merchant was an entrepreneur with full responsibility over risks taken. Risks in inter-city trade, especially in the thirteenth century, were remarkable. At the same time, increase of trade volume would havebenefitedbothforeignandlocalmerchants.Thereforeitwasin thecommoninterestto decrease the risks of being cheated, attacked by pirates, or constrained by local rulers. Later, credit risks were included. However, as in the case of many social situations, a single merchant has neither the incentives nor the means to make investments for provision of the public good in the shape of security of trade. Without an external enforcer, we are faced with the classic problem of an empty promise of punishing the cheated party even in the case of perfect information (see Figure 2).

In Figure 2, Merchant I has two alternatives – to cheat (C) or not (N), and Merchant II in the second stage of the game has two options: to punish (P) by ostracizing or prohibiting further trade or not (N). A simple extensive form game with perfect information indicates the payoff profiles,andit isevident that thestrategy“neverpunish”strictlydominatesover“alwayspunish”andweaklydominatesover“punishwhencheatedandnotpunishwhennotcheated”.Thuscheatingistheoptimalstrategyofthefirstplayer.

Figure 2. Punishment is not a credible threat

Although evolutionary games (Axelrod 1984) justify the emergence of reciprocity and coop-eration in repetitive situations, we assume that independently operating merchants may not belong (at least initially) to the network of repetitive interactions (there were approximately 180 trading places in the Hanseatic League, each having dozens of independent merchants). However, if punishment can be enforced as a social norm in the case of cheating, then Mer-chantIwillchangehisbehaviour.Obviously,thiscommitmenttopunishisbeneficialforthesecond player, and therefore it is very likely that the second player is ready to bear the con-siderable cost (enforcement costs) of making the threat of punishment credible.


49

Greif et al. (1994:756) state that the merchant guild’s strategy is conditioning future trade on adequate past protection, using ostracism to achieve security (rather than privileges or lower prices). We will argue that there is one more important strategy – reputation building. “Thewarofeverybodyagainsteverybody”createdthepreconditionoftheemergenceofanorganizational form like a merchant guild. On the one hand, a guild was caused by individu-alisticorganisationof“commonmerchants”astherewerenoalternativecorporationsforriskbacking and trade mediation. On the other hand, it was caused by the need to enforce credible commitmentby“thecommunitylabel”.Thislabelcouldmakeallthemerchantsfromacer-tain community responsible for the damage created by any member of the community. Thus, as Greif et al. (1994) show, the reputation building of the community was vital and inside the community there was keen surveillance over the behaviour of traders, which made intra-community enforcement mechanisms support inter-community exchange.

4. The solution: the agency model

We will show that agency is an institutional structural solution to the credible commitment problem.Later,wewilldemonstratehowthenarrativesupportsourargument.Butfirstwehave to admit that forming an organization (like a merchant cartel), which will transfer infor-mation,standforthemembersinconflictswithlocalrulers,andmostofall,commitsanctionstowardsitsownmembers,iscostly.Thebenefitsfromtheefficient‘communitylabel’orqual-ity mark are related to the volume of trade accompanied by decreased risks of being cheated. Let us assume that each community member faces a dilemma – the ability to credibly commit to punishment will increase trade volume Σ x(p), where p is the number of people commit-ted and x is the value of traded goods for each merchant. Compared to the model in Figure 2, nowweaddalocalguildbrother(whoisalsoamerchant),thushisbenefitsalsocomefromhonest trade. Sanctions (or Axelrod (1997) metanorms) to make punishment a credible threat are used by the local guild brother. To keep the game as simple as possible, we assume that sanctions are costly. The cost of sanctions is cs. If the discount factor is δ, indicating prefer-encesovertime,andthegameisrepeatedinfinitely,thentotalbenefitsfromsanctioningtheguildbrother are -x[(p)-x(p-1)+c³]x(p)

1-δ .Thismeansthatsanctionswillbenefitfuturetradebuthurt current trade, and of course they are costly. In Figure 3 we substitute the latter three ar-guments by u, so u=x(p)-x(p-1)+cs, which indicates the one time difference of trade volume because of punishment plus the costs of sanctions. If sanctions are not enforced, future trade volumewillbeinfinitelylower,sotheguildbrotherbenefitsstayat

δ−−

1)1( px .

Thus, in the final stage, the guild brother compares two possible discounted payoffs andchooses to sanction if

The value of the left side of the equation is dependent on the discount factor – the more patient agents are (the bigger the discount factor), the higher the probability of sanctions. Although in economics this conclusion seems trivial, due to the static nature of the medieval worldview,itcouldbethattraderswerenotjustaftershorttermprofits.However,thediffer-ence in trade volume x(p)-x(p-1) also matters considerably. In Figure 3, the local merchant’s cardinal preference ordering is also given (the bigger number indicates higher preferences). Ifweassumethatsanctionsarebeneficialtotheguildbrother,then“punishment”(P)isalso


)1()1()( −>−− pxupx δ .

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beneficial,sothatsanctionsmustbeacrediblethreattomakeagencyself-enforcing.Assum-ingthatforeignmerchants’benefitsareX, Y and y accordingly and X >Y (and this is indepen-dent of y)aforeignmerchantchooses“notcheating”(NC)over“cheating”(C),andthegamewillendinthefirststage.Honesttradeisestablished.

The costs of sanctions (cs) must also be considered – the lower they are, the more probable that“sanctions”isadominantstrategy.Thecostofsanctionsdependsoncompliancewiththegroup and this is also dependent on group size. Thus we may argue that restricted access to the merchant guild in early periods was not caused by the cartelization argument, but rather by the information argument – the more optimal the size of the group, the easier it was to enforce sanctions, and to obtain information about possible misbehaviour by members. Due to cost considerations,certainrules(likemembershipbynationality)couldbejustified.Toanextent,itdefinedcommunitiesandfosteredtheirinternalorganizationsimilarlytoothernormsofidentificationsuchasclothingandrituals.ThisobservationisconsistentwithNorth’s(1990)claim that “groups of individuals bound by some common purpose of achieving objectives […]comeintoexistenceand[…].evolve[inresponseto]theinstitutionalframework”.

Willtheresultofourmodel–crediblethreat–findanyempiricalevidence?Althoughthenumber of sources is limited, we can combine a narrative to show that considerable evidence exists to support our model.

5. Back to the narrative: Tallinn Merchant guild in the 14th century

Up to the mid-thirteenth century, a Hansa merchant was an itinerary trader, who travelled in groups and traded by barter (Dollinger 1970:163). Later, this tradition was replaced by an independententrepreneurinchargeofhisownfirm,whoconductedbusinessfromhisoffice


δ−−

1)1( pxupx

−−δ1

)(

Figure 3. Agency in the sanctions and punishing game

51

at home and used representatives or clerks for travelling. A merchant was the owner in many partnerships and this was the standard form of commercial enterprise. Partnerships involved asmallnumberofassociates,foralimitedperiod,andforaspecificproject:

[…]therewasnosinglecommercialfirm,permanent,centralized,having itsheadquarters inaspe-cialbuilding,withsubsidiaryfirms, itsownclerkandagentsandsurviving throughseveralgenera-tions – the sort of business represented for example in Italy […] or in south Germany […] (Dollinger 1970:168).

Transaction costs (costs of using inter-city markets) were therefore relatively low (which is definitelynotthecaseatthebeginningofthetrade)anditseemsthattransactioncostscouldbe lowered by using institutions alternative to the market – a guild or a kontor. The risks in thefirstperiodoftheHanseaticLeagueweremorerelatedtopiracyandsecurityofseatravel;later, credit-risk was included.

A guild is a common organizational feature of all Hanseatic towns, mainly dealing with orga-nizing overseas trade (Hammel-Kiesow 2008). Its relative importance and role varied from case to case, depending on the social power of the princes and the patriciate, on the size of the population, and on a guild’s relative wealth. Our study focuses on the town of Tallinn in the 14th century (see also Figure 1) and we show that in this case the merchant guild (Grosse Gilde) was a cooperative agency which enforced honest trade.

From 1346-1561 Tallinn was ruled by the Teutonic Order. The ruler of the town was not the Grand Master alone but rather the Order as a corporation (Kreem 2002:20). While the rela-tionship between the Order and the Town may not be as unimportant as portrayed by Pullat (1976) and Margus (1939), we consider merchants to be independent players. This follows from the fact that in1346 theTeutonicOrder confirmedall theprivilegesof the citizensgranted by the Danish kings as a part of medieval routine (Kreem 2002:39).

Tallinn’s total trade in 1368 amounted to 99 294 marks (the price of the average stone-built house in Tallinn was 60-80 marks at that time (Kaplinski 1980)). Furs – sable, beaver, lynx, squirrel, and rabbit – all from Novgorod, were in great demand in the Hanseatic League and the amounts imported were impressive – 300 000 pelts between 1403-1415 , 30% of which came through the merchants of Tallinn, the rest through Tartu, Pärnu, and Riga (Dollinger 1970:325). The town remained small. According to sources from the 14th century, the total population of the lower town was approximately 4000 (Mänd 2004). By adding together approximate numbers of participants from the Christmas and Shrovetide festivals based on Mänd (2004: 138-139) we propose that there were altogether more than 200 merchants in the town. If only guild brothers are included (bachelors and non-citizens are not included) the number would have likely been between 70-150 merchants in 1510-1550. Also, it may be as-sumed that the number of guild brothers increased considerably over time (Mänd 2005), and that it was smaller during our period of interest.

By the 15th century, the social career of the merchant in late medieval Tallinn was well for-malised. First the non-citizens and bachelors were accepted into the Brotherhood of Black Heads.Onaverage,a“blackhead”spentfiveyearsinthecorporationbeforebeingacceptedinto the Grosse Gilde. Only merchants could be members of that guild. Although all schras (regulations) of the guild had to be accepted by the city council (magistrate), the guild was


52

ratherindependentinitseveryday“club-life”.TheGrosse Gilde (probably founded in 1363) was the only merchant corporation in Tallinn.

Increasing institutionalization (also formalisation due to increasing literacy) is characteristic of that time. In later periods (in the 15th century), as successful merchants became members of the magistrate, increasingly more initiative in merchant affairs is taken over by the magis-trate. The Hansetag in Lübeck gradually became a gathering of the altermen (members of the assembly) of the magistrate, accompanied by the guild brothers. The magistrate consisted of two (Kotter 1991:8) or four (Kala 1998:31) burgomasters and fourteen aldermen procured for their lifetime. Aldermen and burgomasters received no material reward or exemptions for their service. Only the members of the Grosse Gilde could be elected to the magistrate. Aldermen were divided into 11 different sub-courts (Kala 1998:31), which dealt with town affairs in provision of public goods such as the court, military defence, diplomatic relations, minting, and various constructions. Kotter (1999:76) describes the cost structure of the mag-istrate during 1433-1705, showing that 70% of the town revenues were spent on salaries (usually non-monetary rewards like clothing and footwear) of the magistrate-craftsmen and onother services (suchasmusicians), court expenses, defence, “foreignaffairs” (suchastravelcosts,gifts,officialdinners,lettersandtranslations),building,andrenovation.Alreadyin 1282, the Lübeck town law of Tallinn stated that each burgher had to contribute an annual personaltax(Kala1998:§108).Thetaxconsistedoftwoparts–thepolltax(afixedtaxof1/12 of a Riga mark) and property tax approximately 4-5% of the value of property. The larg-estpartofrevenuescamefromexcisetaxesonbeer(leviedin1454(Jatruševa1986:36))andon export of wine and stones (Kotter 1999). This shows that the town earned directly 15-20% of total revenues on export excise. The wealth of the burgher (the value of his property) was dependentonefficienttraderelations,whilerelianceontradeintownfiscalaffairsisobvious.

Over time, the magistrate increasingly started to coordinate the internal and external affairs of the town, while social ties between the magistrate and merchant guilds were tight. Doll-inger (1970:135) states that government in some towns was practically a family business. This is not true in our case; in Tallinn it was prohibited to elect brothers, fathers, or sons to the magistrate. The aldermen received no salary for their duties, thus had simultaneously to maintain their merchant activities. Aldermen were elected from among the grosse gilde broth-ers, mostly from among brothers who had been an alderman or an assessor of the guild (this indicates that before election they had been members of the merchant guild approximately twenty years (Mänd: 2005:180)). An alderman of the magistrate remained a member of the guild; he did not participate in all of the social events of the guild, although he did participate in the guild’s most important festivals and feasts.

It can be assumed that in the early days of the Hanseatic League, merchants gave an oath of commitment to honest trade, including to pay all customs and tariffs (Hammel-Kiesow 2008).Eventually, certain trade norms called Schras were agreed upon. All of the exclusive rights of “common merchant”weregrantedbycitizenshipofHanseatictowns.Becomingaburgher (citizen) simultaneously meant becoming a member of the guild (Mänd 2005:141, and also Lübeck town Rights 1282). No earlier Schras (if they existed at all) are preserved, but the 1395 schra does not indicate any direct trading principles of the guild, but rather states the requirements for guild brotherhood (and sisterhood). “Everyone who belongs to our guild must be honest and trustworthy” (Nottbeck 1885:40); moreover, it is mentioned that un-


53

tilallconflictsbetweenguildbrothersorothers(itcanbeassumedthat“others”includedHansa merchants) are resolved, a person would not belong to the guild. The Schra states thatthosewho“desecrate”contractswillbeostracized.A 1541 Schra includes a paragraph stating that “if somebody violates general trading principles of the guild, he has to be ex-pelledfromit”(Nottbeck1885:61§93).This isworthstressing,as therightsof“commonmerchant”relatedtotowncitizenshipandmembershipintheguild.The Schra also indicates that a ban was imposed on any illicit trading by non Hansa merchants, and guild members could not belong to other guilds in the same town (Nottbeck 1885:§57). The implication is that the“guild label”wasseenasaguaranteeofhonestyof trade.Ostracisingproblem-aticlocaltradersandacceptance(orat leastaninvitationtoguild“club-activities”(Mänd2005:170)) of all Hansa merchants fromother cities justifiesourmodel.Theoral cultureenforced institutions based on credibility and trust, and reputation building was the most important aspect in efficient enforcement.Most legal procedures reliedonoralwitnesses,onasocialnetworkbasedonreciprocityofcrediblecommitmentto“tellthetruth”.

Although only more recent (from the 17th century) cashbooks of the Grosse Gilde have been preserved and although the Schra from 1395 does not indicate fees other than penalties (main-lyfines)relatedtomisbehaviour,itstillmaybeassumedthatguildbrotherspaidanentrancefeeandaquarterlylumpsummembershipfee(poll tax).“Projectspecific”payments(e.g.related to building the guild house 1406-1417 as well as fees for annual feasts and festivals) were also probable. As the cost of building the guild house, organizing feasts, social security and care, was considerable, it can be assumed that the membership fee was relatively high.

Thenextsectionwilloverviewthegradualdeclineof theHanseaticLeaguefor“political”reasons.AsthebenefitsfromHansatradedeclined,theguildbrothers’incomedecreasedandthe intrinsic reasons for the existence of the Grosse Gilde changed. Protection of the town’s interests against the interests of Hansa merchants or even against other guilds in the town become more important, and membership become increasingly exclusive.

6. Arise of rent-seeking guild: developments from the 1450s to the 1520s

AlthoughTallinnwasstillflourishinginthefifteenthcentury,theperiodwasalreadymarkedby the gradual decline of the Hanseatic community. During this period, monarchical power was being consolidated in Northern Europe, increasing the town’s cost of compliance with the Hansa. Ivan III annexed the great urban republic of Novgorod in 1478. This ended the functioning of the kontor because the Muscovite empire was hostile to foreigners.

Theprivatebenefits that theLivonian townsandmerchants individuallygainedfromeast-bound trade initiated the gradual monopolisation of trade. In 1422, Tartu started to control the kontor and decide who could trade with Novgorod, and in 1459 Riga stopped all foreigners, including Hansa merchants, from trading directly with Polotsk (Dollinger 1970:294). These changes in economic policy and foreign affairs created a bankruptcy wave in Tallinn before the Reformation (Margus 1939:87).

Later, in the 1520s the Reformation began almost at the same moment in all the North Ger-man towns.At first, town councilswere hostile to the new religion: in 1525, the diet of


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Lübeck even passed measures against teaching Luther’s doctrine, but only a few delegates approved it (Dollinger 1970:320). The second diet of the year proclaimed that in religious matters, each town had to decide for itself (Dollinger 1970:321). The Reformation made socialrelationsinTallinnmoreintense–inthe1530s,conflictsbetweenmerchantsandar-tisans often took place (Põltsam 2003:21). In 1526, the craft guilds of Tallinn decided that all who did not support the new religion, and in some cases, even those who visited Catholic masses, were expelled from the guild (Põltsam 2003:22). The reformation, teaching equality of humans in the eyes of God, encouraged craftsmen to defend their rights against the mag-istrate and patriciate (Margus 1939:88). Guilds became increasingly nationally and socially segregated. This indicates that guilds gradually changed their role in the urban community and became unions to protect artisans’ economic interest against merchants and vice versa.

Based on our model and sources (Hammel-Kieslow 2008; Pagel 1942), it can be assumed that, originally, merchant guilds did not restrict access by nationality. Over time, merchant affairs became increasingly institutionalized, merchants were no longer travelling much, and the merchant guild started accepting members from lower social classes to do the travelling for them. Access to town citizenship was, however, restricted for the lower social classes, as one had to live in the town for at least a year and have recommendations in order to become a citizen. In later periods, access to the guild became increasingly restricted and regulated. Estonians were not accepted into the Grosse Gilde; later, the restrictions applied to everyone whoworkedforasalary,andfinally theyalsocametoapply to localshopkeepers(Mänd2005:167). Eventually, non-Germans or workers could not even visit the guild house (Mänd 2004). In the 1528 Schra, an additional paragraph stated that issues discussed in the guild house could not be shared with outsiders (Nottbeck 1885:45).

A century after the creation of social norms embodied in the formal rules of town culture, the role of guilds in the social life of the town had become ever greater, and we can assume that compliance with guild regulations was high. Therefore the enforcement costs of sanctions


δ−−

1)1( pxupx

−−δ1

)(

Figure 4. Optimal versusinsiders’benefitsfromtheprotectingorganization

55

(cs) were low. Individual enforcement costs were now primary direct costs related to the membership fee. Thus average cost (c)wasconstant.Themembers’totalbenefitsfromopti-mal group size n are now smaller than the individually optimal group size n* (see Figure 4). Figure 4 indicates that each individual had to pay a membership fee (c) for entry to the club, andthuswearedealingwithafixedaveragecost.ThetotalbenefitG(n) is now a decreasing function due to the competitive provision of an almost private good now – the bigger the group,thelessbeneficialisthecarteltoasinglemember.Thuseachindividualhasanincen-tive to become a member of the guild as far as cn

G >+1 ,andthisconditionissatisfiedwhen we reach n*. Theinsiders’totalbenefitismaximizedwhen cdn

dG = , meaning that the optimal size of the group is n . As far as nn ˆ* > , insiders have the incentive to limit entry to the guild, as in all monopolistic cases. Is there any additional evidence as to restrictions on entry and increasing secrecy to justify our interpretation? There is some, for example dress codes. Segregation by dress is one additional measure similar to entry restrictions and this was common. However, there is no evidence that dress norms created any tensions in Tallinn before the 15thcentury.Thefirstsumptuarylawregulatingthecostsoffemalejewellerywasimplemented at the end of the 15thcentury(Põltsam2002).Itisdifficulttoassesswhetheritwas the relative cost of clothing that did not make sumptuary codes relevant earlier, or if it was relative compliance with informal dress-codes that was higher until the end of the 15th century. Dress-norms enforce segregation. It is clear that at the beginning of the sixteenth century, urban societies became increasingly formally regulated. However, after 1541 no ad-ditional paragraphs were added to the Schra of the merchant guild concerning honest trade.

7. Conclusions and discussion

More than 100 years is a long period for a case study. Regarding the limited number of origi-nal sources and our ability to perceive the historical context, we assume that the Merchant guilds’ social and economic role in society changed considerably over time. Initially, it was a risk-pegging agency for itinerary travelling merchants, then increasing its social role and finally becoming a rent-seeking cartel.Wedemonstrated that initial institutionalisationofmerchant affairs was self-enforcing by supporting trade and thus also economic growth.

In our case we can say conclusively that by the middle of the thirteenth century the Hanseatics already held a near-monopoly in trade in two seas, and their commerce was organized around the great axis Novgorod-Tallinn-Lübeck-Hamburg-Bruges-London, also enlarging later to southern Germany, Italy, France, Spain, and Portugal. At the same time, the Hansa remained an anomalous institution which can puzzle contemporary political scientists and economists:

It was not a sovereign power, for it remained within a framework of Empire and its members continued to owe some measure of allegiance to many different overlords, ecclesiastical or lay. It was an amor-phousorganization,lackinglegalstatus,havingatitsdisposalneitherfinancesofitsownnoranarmyorafleet.ItdidnotevenhaveacommonsealorofficialsandinstitutionsontheirownexceptfortheHanseatic diet or Hansetag, and even then met rarely, at irregular intervals and never in full strength (Dollinger 1970: xvii).


56

Inspiteofthestructuralweaknessesandtheconflictinginterestsinevitableinanassociationoftownssodifferentandsodistantfromanother,theHanseaticLeaguelastedfornearlyfivehundred years. In 1630, a closer alliance was set up between Lübeck, Hamburg, and Bremen as a substitute for the Hanseatic League. In 1669, the Hanseatic diet met for the last time, andafinalattemptatrestorationprovedunsuccessful(Dollinger1970:xix).Thesecretofits longevity is not to be found in coercion, but in the realisation of common interests bind-ing the members of the community together. The common interest was based on voluntary cooperation, and was not easy to enforce under medieval technological, informational, and institutional constraints.

Our study indicates that the guild acted as a substitute for formal state or legal institutions. While“commonknowledge”amongeconomistsoftenviewsguildsasmonopolisticcartelsorrent-seekingorganizations,Merges(2004)statesthatguildswereefficientinformationtrans-ferees solving the asymmetric information and quality assurance problems in medieval soci-ety. Greif et al.(1994)describemerchantguildsasorganizationsvitalforefficienttrade.Boththe rent-seeking argument and the credible commitment argument demand that organizations fulfil certain criteria: (a) the segregation principle (differentiates insiders fromoutsiders);and (b) shared norms by insiders (Merges 2004:4). We have seen that the role of segregation increased in importance throughout the history of the merchant guild. Various social norms of segregation – by clothing, by profession, or by nationality – eventually appeared. In order to beself-enforcing,normshavetobebeneficialtofollow.Merchantsbenefitedfromaninter-community exchange that included common merchants, but excluded all local shopkeepers and craftsmen, and eventually all non-Germans. Traders applied a principle of community responsibility that linked the conduct of a trader and the obligations of each and every mem-berofthecommunity.Throughdecreasedtradevolume,the“communitylabel”madeallthemerchants from a certain community partly responsible for the damage created by anyone inside the circle. Greif et al. (1994)alsoconfirmthatcommunalpunishmentorsanctionsbecame a credible threat and traders were able to use intra-community enforcement mecha-nisms to support the inter-community exchange. The system created the need for restrictions on membership due to cost considerations which led to constraints such as membership by nationality.Therestrictionsdefinedcommunitiesandfosteredtheirinternalorganizationlikeothernormsofidentification,suchasclothingandrituals.

Institutional studies reveal a variety of reasons that lead to institutional change, but we be-lievethatachangeinprivatebenefitshadanimportantroleinthisgradualchange.Ininsti-tutionalliterature,themostelaboratedcauseofchangeiscalledthe“criticaljuncture”(Pier-son 2002, Rittberger 2003), which can be an unanticipated technological change (Guinnane, 1994), political changes (Greif et al. 1994), or population increase (Hoffmann et al. 1994). In ourcase,privatebenefitschangedmainlyduetochangesinthepoliticalsituationbroughtonby the closure of the Novgorod kontor. Whereas most institutional studies concentrate rather on path-dependency or on the inability to change, we also note the gradual decline of the Hansa, and the gradual transformation of the function of the guilds.

Themostelaboratedcausesofpath-dependencyare“culturalbeliefs”relatedtosomeinstitu-tionalsettlement(Greif1995:23),andvestedinterestorassetsspecificity(Pierson2002:205).Whentheguildasanorganizationwasfirmlyestablishedandfunctioning,thenthenewroleof protection of economic rights was a logical continuum under changed economic and po-


57

liticalcircumstances.Theguildbecamebeneficialforanarrowcircleofinsiders,partlyatthe expense of outsiders. The days of the positive-sum game ended for Livonia and Tallinn.

The most severe criticism of institutional studies is presented by Clark (2007), who states that narratives do not allow for demonstrating universal knowledge or any policy recommenda-tions,becauseeverythingdependsonthespecificculturalandhistoricalcontext.Thishasalsobeen duly noted by one of the promoters of the method, Margaret Levi (2002), who calls the (in)ability to make generalizations the Achilles’ heel of the method. Our case suffers from the samelimitation,butwebelievethatalthoughthespecificgamemaynotbetotallyportableit does yield explanations that can be tested in different settings. As Levi (2002:16) states,

“The comparisons can be done by other area specialists, historians, and others who must con quer languages, archives and other sources to acquire in-depth authority over the subject matter”.Thatiswhyitcanbesaidthatdemonstratinggeneralisabilitymayrestonthewidercommunity of scholars. We also encourage comparative studies about the impact of similar contemporary institutions. Will political change or the current turmoil in the world economic climatetransformourcurrent“guilds”–nationalorother–intoorganizationshostiletonewentrants?Whataboutinternational“guilds”liketheEU?

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Industry relocation, linkages and spillovers across the Baltic Sea: extending the footloose capital model

Ole Christiansen, Dirk H. Ehnts, Hans-Michael Trautwein 1

Abstract

Studying the recent relocation of manufacturing industries from the Nordic countries to the Baltic countries, this paper provides an empirical application of the footloose capital model, a framework for spatial analysis. The model is extended to include input-output linkages and FDI spillovers. It is calibrated and applied, industry by industry, to a 3x3 matrix of Baltic countries and Nordic countries and to the pairing of these blocs. Simulation results are com-pared with ‘real world’ data and discussed in regard to testability restrictions of the footloose capital model. Incorporation of vertical linkages and spillovers can improve the goodness of fit,butwhilethepredicteddirectionofindustryrelocationisoftencorrect,predictedlevelsare not.

Keywords: new economic geography, footloose capital model, linkages, spilloversJEL classification: F120, F140, R120

1. Introduction

In the context of integration of the Central and Eastern European accession countries into the European Union, expectations are high that these countries will achieve faster economic development through inward foreign direct investment (FDI). It is generally argued that the relocation of productive activities from Western economies would create a more vertically differentiated structure of production in Eastern economies, with upstream and downstream linkages between the sectors. This process could generate economies of scale and scope that help to increase aggregate employment, income, and demand. It is also argued that productiv-ityoflocalfirmswouldbeenhancedbyFDIthroughtechnologyspilloversthatcomewithcooperation and imitation.

In general, the ‘footloose capital’ (FC) model of location theory, developed by Martin and Rogers (1995) and extended by Ottaviano et al. (2002) and Baldwin et al. (2003, chs 3 and 5), isasuitableframeworkforstudyingthecausesandeffectsofcross-borderflowsofdi-rect investment. Unlike many other models in the domain of the ‘New Economic Geogra-phy’ (NEG) it is analytically tractable and amenable to empirical studies. However, the stan-

1 Fak.II-VWL, Carl von Ossietzky Universität Oldenburg, 26111 Oldenburg, Germany. Contact: [email protected]; [email protected]; [email protected]; http:// www.uni-oldenburg.de/iw

Industry relocation, linkages and spillovers across the Baltic Sea

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dard formulations of the FC model do not capture the linkages and spillover effects of FDI operationally.FollowingVenables(1996),intermediategoodsaretypicallydefinedasCESaggregates of all varieties of the industrial good (see also Brakman et al. 2009, p. 151). For reasonsoftechnicaltractability,itmaybepracticaltoletallvarietiesofthefinalproductbeinputs in each others’ production. However, this procedure implies that imperfect substitutes are simultaneously treated as complementary goods, both upstream and downstream. This blurs the perspective on changes in output and productivity in a vertical production structure andisnotcompatiblewithinput-outputdata.Thefirstobjectiveofthispaperisthereforetoextend the FC framework by modelling the structure of vertical linkages less restrictively and empirically more operationally.

The second objective is to integrate FDI spillovers. In the NEG literature, spillovers have been modelled in the static terms of Marshallian externalities of regional specialization (Fu-jita and Thisse 2002). Here we set the focus on dynamic spillovers generated by cross-border movementsoffirms.Whilesucheffectshavebeenexaminedinempiricalliteratureoutsidethe NEG domain (see, e.g., Kugler 2006, Javorcik and Spatareanu 2009), they have not - to our knowledge - been explicitly integrated in the FC framework before.

The third objective of our paper is to study industry relocation in the Baltic region of the EU in terms of cross-border movements from the EU-Nordic countries (Finland, Sweden and Denmark) to the Baltic States (Estonia, Latvia and Lithuania). We have chosen these two blocs of countries because we think that empirical application of the FC model extended to include linkages and spillovers generates insights into the dynamics of economic develop-ment in the Baltic region. At the same time, the characteristic mix of similarities and differ-ences within and between these blocs is particularly suitable for bringing out the dynamics at the core of an extended FC model that includes linkages and spillovers.

Why is the Baltic region a suitable test case for application of the extended FC model? The six countries form two distinct groups of three in neighbouring regions around the Baltic Sea. They all have relatively small populations, compared to Russia, Poland, and Germany, the other neighbours on the Baltic shore. Until 1991, the two groups were quite strictly separated in political and economic terms. The Baltic States were part of the Soviet Union, and trade andinvestmentflowsbetweentheBalticStatesandtheNordiccountriesweresmall(Laaserand Schrader 2004). This changed during the 1990s, when the Baltic States (henceforth: the Baltics) regained their independence and started their transformation into Western-style mar-ket economies. At least two out of the three EU Nordic countries (henceforth: the Nordics) are now among the largest trade partners for each of the Baltics. And the picture is even more impressive in terms of FDI. The Nordics are the biggest investors in the Baltics. As of 2009, they together account for about 65 per cent of inward FDI stock in Estonia, nearly 27 per cent in Lithuania, and nearly 25 per cent in Latvia; outward FDI from the Baltics to the Nordics is negligible.

All six countries are members of the European Union. At the beginning of the observation period (in the mid-1990s) all of them had at least an accession perspective. Despite some convergence in the integration process, both groups remain distinct subregions of the EU, especially with regard to their income levels. In 2007, the end of our observation period and thebeginningof thegreatfinancialcrisis,Sweden’sGDPalonewasmore thanfivetimes


63

larger than the aggregate Baltic GDP. In the same year, the Nordic per capita income (PPP-adjusted average) was roughly twice the Baltic per capita income. While the Nordics form the richest subregion in the EU, the Baltics are among the poorest subregions. However, between 1995 and 2007 per capita incomes rose by factor 4 in the Baltics, as compared to factor 1.8 in the Nordics. Finally it should be noted that, even though the outside world tends to regard the Nordics and the Baltics as homogeneous groups of countries, the industry structures and other characteristics (cultural and historical backgrounds) of the six economies are quite heterogeneous. What do these facts imply for analysis of industry relocation in NEG terms? Trade costs arise for exports of goods from one region to the other, but they are not likely to be prohibitive, as distances across and around the Baltic Sea are comparatively short. Nor are trade costs likely to make a strong difference between the countries. EU integration forced countries to bring their economies under the rule of the acquis communautaire. Political barriers to trade and investment - another component of trade costs that would complicate the picture - were thus relatively low and decreasing. Moreover, EU membership (or the prospects of it) should imply some coherence in the data sets.

That the Baltic and Nordic countries have relatively small populations means that they are relatively similar in potential market size - at least in comparison with the other neighbours (Russia, Poland, Germany). This symmetry makes complete agglomeration of industries in one region or country less likely to occur.2 In terms of actual market size, on the other hand, theBalticsandtheNordicsarequitedifferent,asGDPandotherincomefiguresshow-andthe differences were even greater back in the 1990s. This indicates a high potential for capital flowsfromtheNordicstotheBaltics.ThedominantrolethattheNordicsplayintheinwardFDIstocksoftheBalticsshowsthatsuchcapitalflowsactuallytakeplace.Lastbutnotleast,the transition process of the Baltics can be considered as a policy experiment of opening markets. This beds for dynamics in location choices that one would not normally see in more tranquil times. All facts taken together suggest that the two regions should trade with each other to a degree that makes changes in trade composition and the spatial distribution of in-dustrial activities observable. The Baltics and the Nordics appear to be an almost ideal case for testing the predictive powers of the FC model.

The structure of the paper is as follows. In the second section we describe a linear version of the FC model, adapted from the earlier literature. Due to its highly stylized character and to limitations in the data bases, we cannot test the FC model with conventional econometric methods. Yet we use real data for the relevant variables to run simulations of relocation in the manufacturing industries, both in the Nordic-Baltic aggregate and in a 3x3 matrix for the Nordic-Baltic country pairs. In the next section we describe the simulations and present the results for relevant industries. In the fourth section we check on the predictions of the FC model by confronting simulation results with statistical indicators of industry relocation in terms of exports and FDI stock. In the next section we extend the basic setup of the FC model and simulation to include spillovers, and in the following section we do the same for linkages,

2 As explained in the next section, the footloose capital model is an appropriate framework for analysis of this constella-tion, since the exclusion of various non-linearities makes it less prone to extreme solutions than core-periphery models. Yet even in the FC model, strong differences in market size tend to generate extreme solutions.


64

in order to see whether these extensions increase the predictive quality of the simulations. In the last section we conclude that positive FDI spillovers could not be detected, whereas the linkageeffectsappeartobesignificant.

2. A Linear Footloose Capital Model

NEG has developed a variety of models to simulate location of industries. The choice is be-tween models, where workers, capital owners, or just capital units are on the move. For our purposes,amodelwithcapitalflowsappearstobethebestchoice,sincefactormovementsin terms of capital appear to be much stronger than labour migration across the Baltic Sea (Kielyte and Kancs 2000).

Twoalternativeframeworkswithcapitalflowsarethe‘footlooseentrepreneur’andthe‘foot-loosecapital’models.Intheformersetup,ownersoffirmsmovealongwithcapital,i.e.theyconsumetheirincomeintheregionwheretheirfirmsare(re-)located.Werulethisoutonthe basis of realism. Under present conditions, not many shareholders of multinational enter-prises that invest in the Baltics move there. Hence we choose the FC model, in which only capital moves, but not its owners. Moreover, we use the linear setup of the FC model in order to avoid the problems that would come with bifurcations, hysteresis, and other complications of non-linearity. The framework permits us to deal with non-symmetric regions, such as the NordicsandtheBaltics.Twooppositeforcescreateincentivesforprofit-maximizingfirmstomovetoorleavearegion,withtheadditionalinfluenceofefficiency:thepositiveprofiteffectofmarketaccessandthenegativeprofiteffectofmarketcrowding.Thatwayfirmswillnot(except under extreme conditions) agglomerate completely in one region. The smaller region might have a smaller market, but it offers a less competitive environment. Therefore, some firmsfinditmoreprofitabletolocateinasmallregion.Efficiencyalsoinfluencesfirmloca-tioninsofaraslowercoststranslateintohigherprofits.

The FC model is a 2x2x2 model with two regions, two factors of production and two sec-tors - and hence two goods (Baldwin et al. 2003, ch. 5). In our case, the regions are called the Nordics and the Baltics. The two sectors are agriculture A and manufacturing M. Factors of production are labour L and capital K; their owners are in both cases assumed to be geograph-ically immobile. Physical capital can be moved costlessly from one region to the other. So sn, the share of’ world’ capital employed in the Baltics, is allowed to differ from sK, the share of world capital owned by residents in the Baltics. sL is the share of the world endowment of L that is employed in the Baltics. Capital movements across the regions are generated by capitalowners’searchforthehighestnominalprofitr. Since the owners spend their capital income in the region where they live, price index changes in the region where the capital is employed are of no direct concern. This means that even if more capital becomes available in one region through faster growth or a rise in saving, the decision where to put that capital to work is made by the workings of the FC model. Remember that the resulting sn gives us therelativeandnottheabsoluteshareofindustry.Capitalflowsaremodelledthroughthestandard ad hoc’ migration’ equation (see Baldwin et al. 2003, ch. 2). This yields a change in the Baltic share of employed capital, sn. In the following, Nordic variables are denoted by asterisks.

(1)


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The structure of the agricultural sector is kept as simple as possible. The sector supplies a homogeneous good, the A-good, under constant returns to scale, using labour as the only input. The sector is perfectly competitive, and unit costs are eAw, where eA is the technology parameter and w the wage rate. Agricultural wages in the Baltics w and Nordic w* are not equalized, but agricultural goods can nevertheless be traded. The agricultural good A serves as numeraire and it is assumed that eA =1. In the original linear footloose model, workers can switch between industries, which equalises wages. Here, we allow wages to differ between regions.

The manufacturing sector is monopolistically competitive. A range of n firmsproduces adifferentiated M-good of n varieties, such that the total number of varieties (across the two regions) can be written as nΩ = n + n*.ThefirmsuseK exclusivelyasafixed-costinputF (e.g. for setting up a factory), while L is the sole variable input. The total cost of producing x unitsofavarietyoftheM-goodcanthusbeexpressedintermsofalinearfunctionwithfixedand variable costs, F + (w / eM) x, which captures increasing returns to scale. Exports of the M-good to the other region are costly. It is assumed that the costs of shipping one unit of the M-good between the Baltics and the Nordics are τ units of the A-good, and that they are paid by the exporting region.

Preferences are described by the quasi-linear quadratic utility function:

(2)

whereα>0,β>δ>0,xi is consumption of variety i of a manufactured good, and CA is con-sumption of the agricultural good. Preferences in the two regions are identical. Utility optimi-zation produces linear demand for the typical variety j of the manufactured good:

(3)

with

(4)

Demand depends on the own price, ρj, and on the average price P ofotherfirms.Incomedoesnotinfluencedemandduetothespecialformoftheutilityfunction.3 Demand for the agricultural good is determined as a residual. Total demand is (3) multiplied by the number of consumers.

ThetypicalfirmintheBalticsthusmaximisestotalprofitsasfollows:

(5)

3 Baldwin et al. (2003, ch. 5) argue that neglect of income effects has little impact on the logic of agglomeration, and that this form of utility function helps to avoid the exaggeration of market size differences that tends to occur in models with CES utility functions.


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with

(6)

H and H* are the numbers of consumers in each region and p and p are the prices that Baltic firmschargeintheirhomemarketsandintheirNordicexportmarketsrespectively.Asfirmsare assumed to compete in prices, consumer prices of domestic and foreign varieties in the Baltics are:4

(7)

Equilibrium prices are not simply mark-up prices as in other NEG models, but depend on spatialdistributionoffirms.Thereasonisthattradecostsprotectlocalfirmsfromforeign

competitors.Itisassumedthattradecostsfulfilthecondition , such that therecanbetwo-waytrade.Dividingfirms’operatingprofitsbytheinvestedF units of capi-talyieldstherateofprofit:

(8)

Theequilibriumnumberoffirmsisdeterminedby:

(9)

Inthelongrun,capitalismobilebetweenregions.Asfirmsaredefinedbycapitalinput,thedistributionofcapitalandfirmsisidentical.Long-runequilibriumischaracterizedbyano-arbitragecondition,statingthattherearenomoreprofitincentivestomove:

(10)

Thefirstexpressionholds for interiorequilibriawheremanufacturingfirmsare located inboth regions, whereas in the other cases all industry would agglomerate either in the Baltics (n=1) or in the Nordics n*=1.Substituting(8)into(10),using(7),yieldstheprofitdifferen-tial:

(11) Equation(11)closesthemodel.TheprofitdifferentialdeterminesthechangeintheBaltics’share of employed capital as described by equation (1).

4 Admittedly this setting of prices implies the possibility of dumping; for a discussion see Ottaviano et al. (2002), p. 417.


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3. Simulation

The FC model is a highly stylized story in which the world is represented by two regions (or countries), two types of goods, and two production factors. It may be doubted whether it makes sense to run ex-post simulations with this model using data from a sample of 22 out of 99 NACE sectors (group D - manufacturing), of 6 out of 27 EU countries (not to speak oftherestoftheworld),andwithcapitalflowsconfinedtoFDI.Thereareatleasttwopos-siblemechanismsofindustryrelocation.ThefirstworksviaFDIfromoneregiontotheother(though not all statistically observed FDI implies relocation). The second works via ‘inde-pendent’exitsoffirmsinoneregionandentriesoffirmsintheother;forexample,firmsintheNordicswouldclosedown,becausetheycannotcompetewithfirmsintheBaltics.IftheBalticnewcomersarefinancedwithloansorportfolioinvestmentfromNordiccapitalowners,wehaveasecondvarietyofFC.Thisisconsiderablymoredifficulttoidentifyinthedata.Yetwe think that our simulation exercises yield some valuable insights into the potential as well asthedifficultiesofcarryingoutempiricalstudiesbasedontheFCmodel.

We have run our simulations industry by industry, bloc-wise for the regions (Nordics - Bal-tics in the aggregate), but also for all Nordic - Baltic pairs of countries (which gives us nine cases). The partial-analysis character of the FC model, which derives from the suppression of income effects through the choice of a quasi-linear quadratic utility function, may be con-sidered as a general drawback of the model. Yet here it is an advantage, because it permits us to look at changes in the Baltic shares of employed capital in each industry in isolation. The simulations are based on annual data, as no higher frequency was consistently available. The simulation results are driven by the parameters, some of which are permanent while others aretime-specific.

Table 1 lists the parameters of the FC model. The list is not complete, as some parameters are eliminated by way of normalization, while others are only of technical importance. Param-eters a, b, and c, which are not listed above, determine the love for variety. The endogenous variable in the simulation is the relative share of capital employed in the Baltics, sn.

Table 1. List of parameters

Source: own table

We do not change trade costs from year to year in our model in order to avoid results being driven by their changes. For the endowment parameters sK, sL, sn, KΩ, and LΩ, we have used dataforcapitalformationandlabourforcethatareavailablefromnationalstatisticaloffices.Table 2 shows Baltic shares of the combined labour force in 1995, pairwise, related to Nordic


Parameter Explanation τ tradecostsbetweenregions sK Baltic share of owned capital, K sL Baltic share of employed labour, L eM productivity of Baltic manufacturing production (by year) w wage in Baltic region (by year) K Ω absolute value of total capital L Ω absolute value of total labour

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countries. Hence, the share of Estonia in the combined labour force of Estonia and Denmark is 18.4 per cent. Due to asymmetries in the size of populations in the two blocs, the calculated shares do not vary much from year to year; therefore, we take 1995 labour shares as the basis for all calculations, given that our simulations start with the following year.

Table 2. Actual labour shares of the Baltics in the total of Nordics and Baltics, 1995

Source: Eurostat, own calculations

For analytical convenience we assume that the distribution of owned physical capital is equivalent to that of labour, sK = sL. There are, of course, large differences in owned capital stock between the Nordics and the Baltics, due to differences in both the sizes of their econ-omies and their histories. Yet the purchasing-power adjusted incomes from capital, which matter here, may not be all that different. It might also be objected that differences in capital endowmentactuallyinducedthecapitalflows(FDIandothers)thatcouldbeobservedduringthe transition process. However, in the context of the FC model, spatial distributions of capi-tal ownership and capital usage are detached from each other, and shares in capital ownership affect market size only weakly through consumer demand.

The global endowment-value parameters, KΩ and LΩ,havealsobeensimplified.KΩ was nor-malized to 1. In this way, sn becomes an expression for both the share and the absolute number offirms.LΩ is set to 15, so that the share of the manufacturing sector in total GDP amounts to about 20 per cent. Even though this setting is unrealistically low, it is required in order to keep the model open for the possibility of full agglomeration, so that the A-sector is big enough to pay for transport costs.

Note that while endowments matter for the demand side, wages do not. Discussing the loca-tion of single industries in a partial-analysis perspective, it is assumed that wages matter only as a cost factor, and hence exclusively on the supply side. The last parameter is the industry-specifictechnologyparametereM. Together with wage w it determines comparative advantage in the model through Ricardian differences in technology. In the real world, wage differences between the Baltics and other EU regions have played a major role in explaining relocation of industries to the accession countries (EU Commission 2003). Data for wages and productiv-ity are taken from Eurostat as available for the period 1997-2007. Industries are represented byNACEgroups.DatagapsinsomeBalticcasesbefore2000werefilledusingestimates.Whenever plausible, we used average annual growth rates calculated from available values. Inallothercases,gapswerefilledbytheproductivityfiguresofthefollowingyear.

Basedontheseparameterdefinitions,thesimulationyieldstheBalticshareofemployedcapi-tal, sn. Its changes over time indicate industry relocation. The variable sn can be calculated for every NACE group. We think it insightful to select one industry for evaluation of the model.

Denmark (DK) Finland (FI) Sweden (SE)Estonia (EE) 0.184 0.204 0.127

Latvia (LV) 0.273 0.300 0.195

Lithuania (LT) 0.365 0.396 0.271


69

We have chosen NACE 20, the wood industry,5becauseitistheonlysectorthatshowssignifi-cantoutputinallsixcountriesandsignificantFDIstockinallthreeBalticStates.Thischoicemight seem odd, since endowments play a role in this industry. However, Moroney (1975) shows that labour costs and resource endowments are complementary explanations for trade. Endowments of wood are not exhausted but managed, since it is a renewable resource. Also, the wood industry comprises more than wood cutting (but stops short of furniture).

Table 3. Equilibrium values of Sn in industry NACE 20 in per cent, projected and real (wood and wood products), Baltic aggregate

Source: own calculations

Table 3 shows the results for the bloc simulation, where the Baltics are aggregated as one region and the Nordics as the other. Here sn denotes the aggregate Baltic share of total indus-try. Between 1997 and 2002, the equilibrium share of the wood industry in the Baltics rose from around 20.6 to 21.5 per cent. Given that the adjusted share of labour, sL, in the Baltics amounts to 26 per cent, the result does not seem to indicate the expected catching-up. The result does not compare too well with reality, which is shown in the second row. From 1997-2002 we see some catching-up, while from 2003-2007 the Baltic share of industry stagnates.

Table 4 reports the results for the 3x3 country-wise simulations. These are shown in the upper half of the table. For example, the equilibrium industry share of Estonia in relation to Den-mark is 9.4 per cent in 1997, rises slightly to 10.9 in 2002, and falls to 9.2 in 2007. The real share of industry is calculated by dividing the Baltic country’s production by the combined production of the two countries and is given in the lower half of the table. We see an increase in the share of the Baltic country vis-à-vis the Nordic country in all rows. This increase is much more pronounced in the real world data than in the simulated data. It should be kept in mind, though, that the simulations pertain to long-run equilibrium values, whereas the real dataalsoreflectshort-runfluctuations.

A major cause for discrepancies between the simulated and real data is certainly to be found intheforeignborrowingthattookplaceintheBalticspriortothegreatfinancialcrisis,whichstarted in 2007. Foreign borrowing increased local demand and corresponding wage rises, almost a doubling of wage levels between 2002 and 2007, entered the simulations with the effect of pushing industry away from the Baltics, when in reality it tended to pull industry towards these countries due to a relative increase in demand. It should be noted that there is a certain trade-off between applicability of the FC model to real world data, as compared to NEG models that include demand effects in terms of circular causation, and the neglect of de-mand effects in the FC model. On the other hand, the statistical demand effect of 2003-2007 should not be overrated, since a large fraction may be of a transitory nature. The partly drastic adjustments in the external accounts (in particular of Latvia) that took place in the wake of the global credit crisis, may - once the post-2007 data become available - change the picture towards stronger parallelity in the real data and the simulation results.

Countries 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007projected 20.6 20.8 20.8 19.9 21.5 21.5 21.2 21.2 21.2 20.8 20.6real 5.4 6.2 7.2 8.9 10.0 11.6 15.5 13.9 15.1 15.0 15.6


5 NACE 20 includes manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials.

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Withrespecttothequestionofblocversuscountrysimulations,wefindthatresultsvary.Ifcountries are grouped in a bloc, much valuable information is lost due to aggregation. The correlationcoefficientisjust0.34forthebloc-wisesimulation,lowerthananyofthecountry-wisesimulationcoefficients.Thecountry-wisesimulationsyieldresultsthatinmostcasesfitreasonably well.

4. Foreign Direct Investment and Exports

To check the predictions of the FC model, we confront them with statistical indicators of industry relocation. As discussed in earlier sections, we assume that a positive change in sn correspondswithasignificantinflowofFDI6 in the respective industry, and that a high value of sn correspondingly implies a relatively large stock of Nordic FDI in the Baltics. Moreover, an increase in sn should normally go along with a rise in exports of the same industry. Finally, comparing the changes in sectoral output in both regions should also give a clue about the validity of the model. Here we set the focus on the wood industry in Latvia, as sectoral FDI data were available only for this country, in time series that are consistent only until 2004.

As Table 4 has shown, the model predicts industry relocation from all three Nordic countries to Latvia in the years 1997-2003. The extent of industry relocation seems to be the biggest in the case of Sweden. Firms from both Finland and Denmark are predicted to relocate at a lowerrate.Inabsoluteterms,industryrelocationfromDenmarktoLatviaismostsignificant.

Table 4. Simulated equilibrium and real values of sn in the industry NACE 20 (wood and wood products) in per cent


Sn proj 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007EE-DK 9.4 9.3 9.5 9.4 10.0 10.9 10.6 9.8 8.5 9.3 9.2EE-FI 8.6 10.1 10.4 10.1 12.7 12.7 12.0 11.8 11.3 10.3 9.0EE-SE 0.0 1.6 1.7 1.8 2.8 2.6 2.5 0.0 1.7 0.6 0.0LV-DK 24.3 24.1 24.3 23.7 27.7 25.1 25.3 24.7 25.4 24.1 24.3LV-FI 24.5 25.9 26.2 25.4 31.4 27.9 27.7 27.7 29.3 26.2 25.1LV-SE 11.8 13.5 13.6 13.3 17.7 14.0 14.3 15.2 15.8 12.6 11.0LT-DK 30.7 30.5 30.7 30.6 34.5 33.0 34.0 33.5 32.9 32.0 30.8LT-FI 34.4 32.8 33.1 32.8 38.7 36.3 36.9 37.0 37.2 34.5 32.1LT-SE 15.9 17.6 17.7 17.8 22.2 19.5 20.7 21.7 20.9 18.1 15.2Sn real 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007EE-DK 11.9 13.8 16.3 18.5 21.9 27.3 29.3 31.5 32.8 33.9 35.3EE-FI 4.8 5.7 6.6 7.3 8.9 11.0 11.7 13.1 14.7 13.6 14.2EE-SE 3.1 3.9 4.5 5.2 6.7 8.2 8.8 9.8 10.9 11.1 11.0LV-DK 17.2 19.7 22.9 28.2 27.8 31.5 33.7 35.9 35.9 37.8 40.0LV-FI 7.2 8.5 9.7 12.0 11.9 13.2 14.0 15.5 16.5 13.2 16.8LV-SE 4.7 5.8 6.8 8.7 9.0 10.0 10.6 11.7 12.3 12.8 13.1LT-DK 9.4 8.6 10.3 13.7 16.4 19.9 22.2 23.8 25.5 26.4 28.6LT-FI 3.7 3.5 4.0 5.2 6.4 7.6 8.3 9.3 10.8 9.9 10.8LT-SE 2.4 2.3 2.7 3.7 4.8 5.6 6.2 6.9 7.9 8.0 8.3


6TherearedifferenttypesofFDI,suchasgreenfieldFDI,M&A,andjointventure;notallofthemareconnectedwithindustry relocation. However, disaggregated data were not available.

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If we compare this with the data displayed in Figure 1 we see that the model does not fare too badly, at least in regard to signs of change. Exports and FDI increased in relation to all the Nordic countries.

Figure 1. Exports (continuous line, left scale) and FDI stock (dotted line, right scale) in the Latvian wood industry, in million euros7

Source: Central Statistical Bureau of Latvia

Rates of change, on the other hand, differ significantly. Danish FDI has increasedmorestrongly than predicted, in line with exports to Denmark. Exports to Sweden rose much more (in absolute terms) than FDI from Sweden. Exports to and, in particular, FDI stock from Finland are much smaller than one would assume from the simulation. These differences are certainly explained by market structures not captured by the model, and probably also to some extent by calibration of various parameters. It is also quite plausible that Finnish FDI and trade have been concentrated in Estonia, due to proximity - not only in distance, but also in language and other cultural aspects. Accounting for these links by a reduction of relative trade costs between Finland and Estonia would improve the result of the prediction.

Looking at the growth of simulated equilibrium values of sn between 1997 and 2003 in Lat-vian industry NACE 20, it is interesting that the value is highest in relation to Sweden (21.2 percent,comparedto4.1forDenmark,and13.1forFinland).Thisisreflectedinthedata.Swedish imports and FDI are rising faster than those of the other Nordics. The data also sup-port the more general predictions about industry relocation from the Nordics to the Baltics. In table5wefindthatoutputgrowthintheBalticsoutperformsthatoftheNordics.Hence,wecan conclude that there is a relative increase in production in the Baltics. Summing up, the exampleofthewoodindustryappearsroughlytoconfirmthepredictionsoftheFCmodel.Itwould be interesting to add spillovers and linkages to the model to see if interactions between multinationalsandlocalfirmshaveanyeffectonindustrylocation.


250

200

150

100

50

0199919981996 1997 2000 2001 2002 2003 2004

net exports DK net exports FI net exports SEFDI stock DK FDI stock FI FDI stock SE

7 Annual mean values for 1996-98 in terms of DM/LVL, recalculated by 1 EUR = 1.95583 DM.

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Table 5. Output in million euros, NACE 20

Sources: Eurostat, Central Statistical Bureau of Latvia, own calculations

5. Spillovers

Theoccurrenceof technology spillovers is apossible sideeffectof cross-borderflowsofcapital. In such cases, technology is transmitted from newly arriving multinational enterpris-estodomesticfirms.ThereisalargeliteratureaboutspilloversfromFDI,mostlybasedonstandard neoclassical and endogenous growth theories (Javorcik 2004 provides an overview). The Baltics are quite small, so we treat them as regions. We limit the model to intra-regional spillovers and linkages since there are no data on inter-regional trade and input/output rela-tions for the Baltics. The simplest and most direct case is a pure technological spillover from anarrivingfirmthataffectstheproductivityoflocalfirms.Productivityoflocalandnewlyarriving(foreign)firmsshouldconvergeasmorefirmsmovefromoneregiontotheother.In-clusion of technology spillovers changes the dynamics of the model (of section 3) as circular causationbecomespossible.AsimplemodificationoftheproductivitymeasurethatkeepstheFC model tractable is necessary:

(12)

The change in hence depends on the change in sn, i.e. productivity reacts, with a lag, to relocation. Positive technological spillovers can be expected if sn has risen and foreign productivity e*

is higher than domestic productivity eM.Thisisofcourseonlyafirstapproxi-mation, since the lag structure may differ in reality and other determinants may play a role. Moreover, we have assumed that wages do not immediately adjust.

We tested for spillovers, starting from the case of Latvia again. In addition to NACE 20 (wood industry) we selected NACE 31 (electrical machinery and apparatus), since horizontal spillovers should be stronger in high-tech industries, as compared to low-tech sectors.

Table 6 describes the changes in the location of industry in NACE 20 and 31 for the case of Latvia and Finland. There should be a feedback in the sense that simulation of the FC model including yieldsadifferentconfigurationofindustrylocationsn. Nevertheless, if tech-nologyspilloversareincludedintheFCmodel(FCTS),locationoffirmsinbothNACE31andNACE20doesnotchangesignificantly.Possiblyourextendedmodelunderestimatestheeffects of spillovers, as the latter might not be linear functions of the presence of multination-alfirms.InNACE31theactualsizeoftheindustryinLatviaissosmallthatspilloversmightbe hard to detect, if they occur at all. Our time series may also be too short to account for the lags that typically exist between the arrival of FDI and their effects. Barrios et al. (2005) foundthattheneteffectfromtheentryofmultinationalenterprises(MNEs)isnegativeatfirst

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 changeDK 1,644 1,745 1,744 1,864 1,807 1,748 1,788 1,865 2,023 2,174 2,339 1.42EE 221 290 339 423 505 656 740 859 986 1,116 1,276 5.77LV 341 428 519 734 697 805 909 1,043 1,135 1,322 1,557 4.57LT 170 165 201 296 355 435 510 582 694 782 936 5.51FI 4,410 4,603 4,820 5,387 5,186 5,303 5,608 5,679 5,728 7,120 7,699 1.75SE 6,873 6,946 7,143 7,686 7,062 7,338 7,688 7,883 8,091 8,981 10,350 1.51


M

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Table 6. Simulated equilibrium and real values of Sn in industry NACE 20 (wood) and NACE 31 (electrical machinery and apparatus)


andthenturnspositiveasmoreandmoreforeignfirmsarrive;inadditiontotime,thenumberand share of MNE in the industry may thus play a role. In contrast to other studies, wages adjust to changes in productivity with a lag of one year and erase competitive advantages.8 In theend,wefindnoproofofhorizontaltechnologicalspilloversfromFDI.Thisisinlinewiththe results of other studies, but it could also be due to limitations in the data.

6. Linkages

Industries are not autonomous, but trade goods with each other. The output of one industry might be the input of another. Following Hirschman (1958), this constitutes a vertical link-age.Theinput-outputflowsthroughsuchverticallinkagesmightchangewhenforeignMNEsarrive(seefigure2).

Assuming that FDI takes place in industry B, there might be a rise in domestic demand in a sector that provides inputs to the MNE (backward linkage to industry A). On the other hand, the MNE might provide a cheaper input or new variety to a downstream sector (forward link-agetoindustryC).Sincefirmsmakinginvestmentsabroadareonaveragemoreproductivethandomesticfirms(cf.Melitz2003),weexpectinwardFDItohavepositivelinkageeffects.As pointed out in the introduction, existing versions of the FC model use CES aggregates of all varieties of the manufactured good as intermediate goods. In our view, this procedure does not (appropriately) takeaccountofvertical linkages,as theycanbe identified from input-output tables and other relevant data, so we develop two different approaches to incorporate linkages into the FC framework.

Thefirstapproachtakesaccountofbackwardlinkages,asdescribedinfigure2bythesup-plies of inputs for industry B by industry A. We assume that a rise in the Baltic share of firmsinindustryB, , feeds back to industry A. Increased local production in industry B raises demand for inputs from industry A, affecting the prices in that industry. For the sake of simplicity, we assume that the maximum rate of price change corresponds to the share of the deliveriesofAtoBinthetotalproductionofA.Ahigherpriceleadstohigherprofitsintheregion,whichattractsfirms.

Countries model 1999 2000 2001 2002 2003 2004 2005 2006 2007LV-FI FCTS 0.26 0.26 0.32 0.26 0.28 0.28 0.29 0.26 0.25NACE 20 FC 0.26 0.25 0.31 0.28 0.28 0.28 0.25 0.25 0.25

real 0.10 0.12 0.12 0.13 0.14 0.16 0.17 0.13 0.17LV-FI FCTS 0.25 0.22 0.27 0.26 0.28 0.25 0.24 0.22 0.20NACE 31 FC 0.24 0.23 0.26 0.26 0.27 0.26 0.25 0.23 0.21

real 0.02 0.02 0.02 0.03 0.03 0.03 0.04 0.05 0.04


8 A feedback to the demand side would result, which is not modelled here. It would be interesting to pursue this road in future research.

74

The new price of a variety is described by

(13)

The right-hand part in brackets represents the rise in price caused by changes on the demand side.ε,thepriceelasticityofdemandforaspecificinput,affectspricingofthefinalgood.We demonstrate this with an example. In Estonia, the wood industry (NACE 20) gets inputs from NACE 26 (manufacture of other non-metallic mineral products) that amount to about two percent of the latter sector’s total output. Now we need to make some assumption about how changes in demand translate into prices. Therefore, we posit that changes in NACE 20’s demand for a NACE 26 product can change the price of that product in the range of -2 to +2 per cent, so that є=0.02. If all the wood industry is located in the Nordic country Sn = 0, equation (13) yields the original price multiplied by 0.98. For the Nordic country, the mul-tiplier would be 1.02 (see equation (7) for the original version). The bracket on the right of equation 13 is only there to get a multiplier of . If the wood industry is distributed symmetrically , the multiplier takes on unit value. A higher price is positive for thefirmsintheregion,sinceitscostsdonotchange.Thismeansthatprofitsrise.

Table 7. Simulated equilibrium values of Sn, in per cent, industry NACE 26 (Manufacture of other non-metallic mineral products)


Table 7 shows the results for the case of Estonia and Finland. The extended model (FCBL) features backward linkages. It predicts an Estonian share in NACE 26 that is lower than thatofthebasicFCmodel.In1997,theshareoffirmsofNACE26locatinginEstoniaispredicted to be 7.8 per cent (FCBL) against 11.0 (FC) and 5.7 (reality). The reason for this discrepancyisthebackwardlinkage:AsfirmsinNACE20arepredictedtobemostlylocatedin Finland (and the other Nordics),9 that region enjoys the advantage of higher local demand

Countries model 2000 2001 2002 2003 2004 2005 2006 2007EE-FI FCBL 7.5 7.7 8.5 9.3 9.5 8.7 9.0 8.6

FC 10.4 10.4 11.1 11.9 12.1 11.3 11.8 11.5real 6.3 6.9 7.7 8.7 9.8 10.8 14.5 13.7

Figure 2. Linkages and spillovers resulting from foreign direct investment

Source: own graph

input outputspillovers

FDIinow

backwardlinkages

industry A industry B industry C

forwardlinkages


75

from NACE 20. Firms in NACE 26 are more inclined to choose Finland as it is a larger region. TheFCBLmodelconsequentlypredictsalowershareofNACE26firmsinEstoniathanthebenchmark FC model. This works at least as long as the Baltic share in NACE 20 is lower than 50 per cent.

The second approach is based on the argument that the number of suppliers in one region is inversely related to the price of their product. We now consider the output of industry B as intermediate goods that serve as inputs for industry C. If the number of domestic producers in B, sn, isrising,firmsin industryCshouldbenefitfromadeclinein its inputprices.Toinclude this effect, a second manufacturing sector that produces an intermediate M-good is added, whereas the original sector produces a consumer M-good. For the sake of simplicity, theFCmodel’soriginalproductionfunctionisminimallymodified.Anincreaseinsn in the intermediate industry translates into a lower price index in that region.

(14)

The price index pI is formed by weighing the product prices of domestic (phh) and foreign (phf) intermediate goods in the domestic market. The same is done to calculate the price index in the foreign region pI*.

It is an implicit assumption here that consumer good producers (industry C) need all varieties of intermediates (industry B). In our model, we have an external sector delivering intermedi-ates, thus avoiding the problem with CES aggregates that we described in the introduction. TheregularlinearFCmodelsufficestogeneratenumericalsolutionsofprices.Theconsumergoodsproducingsectorisredefinedbytwoequations.First,thepriceoftheconsumergoodis now also dependent on the price index. Second, the return to capital is adjusted to include the costs of the intermediate good:

(15)

where sig is the share of the intermediate in total output. Using data from input-output tables, the resulting costs of intermediate goods can be calculated as:

(16)

(17)

It is thus possible to analyse the effects of FDI on forward linkages in the FC model. If the intermediate industry in one region expands, increased competition will drive down prices. This lowers production costs in the consumer goods industry. However, applying the FC model with forward linkages (FCFL) to our previous examples, industries NACE 20 and 31, doesnotchangetheresultssignificantly,sinceonly20and27percent,respectively,oftheiroutput is used as inputs of other manufacturing industries. Hence a more obvious case of forward linkages was chosen: Textiles (NACE 17) make up for 38 per cent of the production


9TheshareoffirmsofNACE20intheBalticregionthatweusedisanaverageofthethreeindividualsharesoftheNordic countries.

76

of wearing apparel (NACE 18). This is a classic vertical linkage where one would expect an influenceofthepricesofoneindustryontheother.

We have calibrated the FCFL model for Latvia in the period 2000-07 based on a 1998 input /output table from Latvia’s CSB 2003. Earlier data on productivity in the Baltics is not avail-able. The results are given in table 8, where they can be compared to the original results of our simulation. Note that equilibrium values of sn in the FCFL model are lower than in the benchmark FC model. This is because the intermediate industry is located mostly in the Nor-dics, which lowers the input costs of that region’s intermediate products there. Only if the relatively small Baltic economies were to succeed in attracting a share of the textile industry that exceeds their share in total labour would they gain competitiveness in the wearing ap-parel industry.

Table 8. Simulated equilibrium values of Sn in industry NACE 18 (wearing apparel)


Inclusion of forward linkages tends to produce a less positive result for the Baltics because the home-market effect, which normally plays against them, gains in strength. This down-ward correction seems realistic from 2000-2003, at least in the case of Latvia versus Denmark andFinland.In2004-2007theFCmodelisthebetterfit.ThecaseofLatviaversusSwedenfails spectacularly.

Wehavediscussed twoextensionsof theFCmodel.Thefirst featuresbackward linkages,the second forward linkages. Both work to the effect that the region with a higher share of industry in the upstream/downstream sector gains more industry than in the benchmark FC model.Thetransmissionchannelisprices,forinputsinthecaseofforwardlinkages,forfinalproducts in the case of backward linkages. Inclusion of vertical linkages creates an additional agglomeration force, as suggested by Venables (1996). In our case this new force works against the Baltics and lowers their share of industry compared to the basic FC model. Our empiricalfindingssupportsomeofthepredictionsfromthemodel.

The implication of the FCVL models is that the arrival of an MNE in the Baltics should have positive effects on upstream and downstream sectors through price effects. Most FDI would thusinducemorefirmstoenterup-ordownstreamsectors.Thisfollow-upmovementwouldin turn generate another round of feedbacks. The effects are cumulative, as they are all ad-vantageous to the receiving region’s industries. In the end, the arrival of a MNE could trigger a‘FDIwave’ora‘relocationwave’.Ifthresholdvaluescanbeidentified,themodelmight

Countries model 2000 2001 2002 2003 2004 2005 2006 2007LV-DK FCFL 0.13 0.17 0.12 0.15 0.15 0.14 0.14 0.13

FC 0.20 0.22 0.18 0.21 0.21 0.20 0.20 0.18real 0.14 0.14 0.15 0.17 0.20 0.21 0.27 0.29

LV-FI FCFL 0.19 0.23 0.18 0.19 0.18 0.19 0.19 0.19FC 0.24 0.27 0.23 0.25 0.23 0.24 0.24 0.24real 0.18 0.17 0.17 0.19 0.22 0.24 0.26 0.27

LV-SE FCFL 0.06 0.11 0.07 0.04 0.00 0.01 0.00 0.00FC 0.13 0.18 0.15 0.11 0.08 0.08 0.08 0.08real 0.26 0.29 0.26 0.27 0.30 0.29 0.36 0.36


77

be able to explain the volatility of FDI. Our time series are too short to provide any evidence in that respect.

7. Conclusion

Some interesting results emerge from our attempt to apply the FC model to an empirical study. In general, the model is suitable for describing important aspects of the economic integration of theBalticsand theNordics.There iscontinuouschange in thedistributionoffirmsbe-tweenthetwogroupsofcountries.Someofitmaybeduetofastergrowthofnewfirmsand/oroutputperfirmintheBalticcountry,butmuchofitcanbeexplainedbytheactivitiesofMNEsintermsofFDIflowsfromtheNordicstotheBaltics.WehaveappliedtheFCmodelin two ways: bloc-wise and pair-wise simulations. The country-by-country results were more pronounced and corresponded better to the real data. The bloc simulations delivered a ‘one sizefitsall’result,suggestingthattheBalticswerenottreatedverydifferentlybyfirms.Thisdoes not accord with real data. Even though the Baltics are small, it seems important to treat them as separate entities when calculating the distribution of industry locations. We encoun-tered various problems in the empirical application of the FC model. Due to data restrictions, relevant parameters were hard to come by.

Empirical research on technology spillovers and so-called vertical spillovers is normally con-ducted by using a growth theory framework. We have come up with a new approach by using a NEG model which we amended to feature spillovers and linkages. The two categories of secondary effects of FDI can be separated analytically, and the simulations that have been redefinedaccordinglyyieldtheexpectedresults.AsinmostoftheempiricalliteratureonFDIspillovers,wehavenotdetectedanysignificantpositivespilloversfromFDIintheBaltics.This may also be due to limitations in our data, given that we have only short time series for the economies in question. The quality of our simulations can be improved by incorporating vertical linkages. The Baltic share was predicted to be lower in all industries due to the fact thattherelevantdownstreamorupstreamfirmsweremostlylocatedintheNordics.Inindus-trieswhereI/Olinkagesaresignificant,thearrivalofMNEsisgenerallyexpectedtocreatebenefitsfordown-andupstreamfirms.However,ourresultsleadtothetentativeconclusionthat the speed of such processes is slowed down by the relatively large weight of the linkages that MNEs have in their home countries.

Thesupply-sideeffectsofinwardFDIflowsandproductivitygrowthintheBalticsarepossi-bly limited by the size of their home markets. Our model indicates that, due to this limitation, expectationsoffastereconomicdevelopmentthroughFDIinflowstotheBalticsmighthavetobemodified.Intheperiod2002-07,themarketsintheBalticsapparentlygrewatmuchhigher rates than predicted by our long-run oriented model. Yet much of the market growth in the real data was fuelled by foreign borrowing exposed as unsustainable after the outbreak of the great credit crisis in 2007. It remains to be seen in the real-world data of the subsequent fiveyearswhetheractualadjustments in theexternal relationsof theBaltics(inparticularLatvia) lead to a greater convergence with the model predictions in the long run.


78

References

Baldwin, Richard, Rikard Forslid, Philippe Martin, Gianmarco Ottaviano, and Robert-Nicoud, Frédéric (2003). Economic geography and public policy. Princeton: Princeton University Press

Barrios, Salvador, Holger Görg and Eric Strobl (2005). “Foreign direct investment, competi-tionandindustrialdevelopmentinthehostcountry”,European Economic Review 49(7), 1761–1784

Brakman, Steven, Harry Garretsen and Charles van Marrewijk (2009). “The New Introduc-tion to Geographical Economics“, Cambridge: Cambridge University Press

Central Statistical Bureau of Latvia (2003). Input/output tables for Latvia 1998. RigaEUCommission(2003).“Impactofenlargementon industry”,Commission Staff Working

Paper 234Fujita, Masahisa and Jacques-François Thisse (2002). ‘Economics of agglomeration: cities,

industrial location, and regional growth’, Cambridge: Cambridge University PressHirschman, Albert O. (1958). ‘The strategy of economic development’, New Haven.Javorcik, Beata Smarzynska (2004). “Does Foreign Direct Investment Increase the Produc-

tivityofDomesticFirms?InSearchofSpilloversThroughBackwardLinkages”.Ameri-can Economic Review, 94(3), 605–27

Javorcik, Beata S. and Mariana Spatareanu (2009). “Tough Love: Do Czech Suppliers LearnfromtheirRelationshipswithMultinationals?”.Scandinavian Journal of Econom-ics,111(4), 811–833

Kielyte, Julda, and d’Artis Kancs (2002). “Migration in the Enlarged European Union: Em-piricalEvidenceforLabourMobilityintheBalticStates”.Journal of Baltic Studies, 33, 3, 259–279

Kugler, Maurice (2006). “Spillovers from foreign direct investment: Within or between in-dustries?”.Journal of Development Economics, 80(2), 444–477

Krugman, Paul (1998). “Space: The Final Frontier”. Journal of Economic Perspectives, 12(2), 161–174

Laaser, Claus Friedrich, and Klaus Schrader (2004). “The Baltic States’ Integration in the EuropeanDivisionofLabor”.Kiel Working Paper No. 1234, Kiel Institute of World Eco-nomics

Martin, Roger and Carol Rogers (1995). “Industrial Location and Public Infrastructure”.Journal of International Economics, 39, 335–351

Melitz, Marc (2003). “The Impact of Trade on Intraindustry Reallocation and Aggregate IndustryProductivity”.Econometrica, 71(6), 1695–1725

Moroney, John R. (1975). “Natural resource endowments and comparative labor costs: A hybridmodelofcomparativeadvantage”.Journal of Regional Science, 15(2), 139–150

Venables, Anthony J. (1996), ‘Equilibrium Locations of Vertically Linked Industries’, Inter-national Economic Review 37(2), 341–59


79

Book Review

Economic prosperity recaptured: the Finnish path from crisis to rapid growth.

Seppo Honkapohja, Erkki A. Koskela, Willi Leibfritz, and Roope Uusitalo, 2009. MIT Press. Hardback: ISBN 978-0-262-01269-0.

Finland’s economic performance from the mid-1990s has been remarkable in spite of its hav-ingsufferedaseverefinancialcrisisatthebeginningofthe1990sleadingtotheeconomy’sworstrecession.HowcanweexplainFinland’ssuccessinnegotiatingtheperilsoffinancialturmoil and concomitantly transforming itself into a high technology economy?

Economic prosperity recaptured: The Finnish path from crisis to rapid growth tackles the topic head-on. Seppo Honkapohja, Erkki A. Koskela, Willi Leibfritz, and Roope Uusitalo write a concise volume building on the authors’ previous work (e.g. Honkapohja and Koskela, 1999) and also advancing fresh insights. The authors tell stories short and tall, meeting with considerable success in throwing light on Finland’s experience.

The book contains seven chapters. Following the introduction in Chapter 1, Chapters 2 and 3 deal with the crisis and related policy mistakes. The country escaped the 1970s oil crisis rela-tively unharmed mainly due to agreements with the Soviet Union, and following a period of disinflationpursuedliberalisationandderegulationpoliciesduringthe1980s.Butreformingandliberalisingledtoanoverheatingeconomy–inflationdoubledbetweenthemid-1980sand 1990 - which subsequently collapsed at the beginning of the 1990s. The downturn was worsened by the parallel disintegration of the Soviet Union; the authors estimate that the Soviet demise accounts for roughly 3% of the 7% GDP decline in 1991. Finland’s collapse was followed by recovery and a successful transition to a high-tech, thriving economy from the mid-1990s.

The Finnish crisis of the 1990s is rather similar to events in Mexico during the 1994-1995 ‘Tequila crisis’, Asia during 1997-1998 (beginning with the Thai baht’s devaluation in 1997), Russia in 1998, Brazil in 1999, Turkey in 2000, and Argentina in 2002. Finland’s crisis evolved from various factors, including an increasing private sector debt alongside capital flowsencouragedbyahigherdomesticinterestrateinrelationtoforeignrates.

Finland also had debt and illiquidity problems. Furthermore, the country’s monetary policy stance gave the impression that the exchange rate could be kept stable, which was a further factor encouraging bubbles in real estate and other asset prices. But these monetary and ex-change rate policies were unsustainable: Finland devalued the markka in November 1991 and floatedthecurrencyinSeptember1992,adoptinganinflationtargetingregime.Inexplaining

Book review

80

historicmonetarypolicysettinginFinland,thestudycouldhavebenefitedfromrunningaformal econometric exercise. Empirically estimated reaction functions can provide valuable information for discussing monetary policy.

The book does explain other important mechanisms operating during the crisis. Increasing bank lending tends to precede crises, as was also the case in Finland. The conclusion arises from empirically estimating a consumption function revealing that credit growth contributed to private consumption growth and collapse before and after the crisis. Econometric model-lingindicatesthelikelyexistenceofthresholdeffectsintheimpactfromfinancetoconsump-tion, but the analysis does not attempt to explore that feature of the data.

The 1991 banking crisis ended up costing around 7.5% of GDP in 1992. Growing bank lend-ing was not the problem itself, but regulation and supervision did not advance at the same pace, and banking surveillance only improved after 1991. As a result of the crisis, the banking system was reformed and wide-ranging restructuring took place. The stabilisation attempt alsobenefitedfromFinland’scentralisedwagebargaining.Thebookalsodrawsattentiontothe positive role of labour market training programmes in setting the stage for the economy’s recovery and subsequent take-off.

Chapter 4 focuses on the growth and structural changes following the crisis. Globalisation isathemeinthechapterandFinlandhasbenefitedfromopportunitiesarisingfromthein-creasing volume of global trade. The study explains productivity growth as resulting mainly from changing total factor productivity (TFP). TFP growth contributed to rapidly closing the outputgaparisingfromthefinancialcrisis.

But not all recoveries from crises rest on higher productivity growth and economic transfor-mation. For instance, the Dominican Republic, a small emerging market economy, suffered a banking crisis with events similar to those occurring in Finland (Sánchez-Fung, 2005). As is often the case, the subsequent recovery was mainly consumption-based and fuelled by an appreciating currency after initial overshooting in the 2003-2004 crisis.

So what was behind Finland’s ability to recover from the crisis while concomitantly becom-ing more competitive on the basis of technological advance? Chapter 5 explains the impor-tance of human capital in the Finnish recovery. The investigation explicates that Finland was preparedtobenefitfromtheturningtideasithadaqualifiedlabourforce.Infact,educationalattainment measured using average years of formal schooling has been increasing during the last three decades. Engineering education is of good quality and appears to be a factor in explaining the economy’s transformation. But, unlike countries such as India that also have a strong technology-focused tertiary education system, Finland has been preparing from more basic levels and the country performs very well in standardised tests. Results for 15-year old Finnish children in the Program for International Student Assessment (PISA) examinations consistently top the rankings in sciences and math.

Chapter 6 focuses on the leap towards a technology-driven economy. Information and com-munication technology spearhead Finland’s growing prominence in the international econo-my and comprise a large amount of the country’s exports. Government-supported and private investment in research and development has been critical for the success of Finland’s techno-


81Book review

logy ventures -the National Technology Agency (TEKES) has been an important institution in allocating funding.

The case of Nokia is revealing: the company was successful in transforming from its origins manufacturing cables, metals, and rubber products to being a powerhouse with the largest share in the global cellular phones market. It is worth noting the extent to which the com-panyhasbenefitedfromgovernmentfinancialbacking.ThebookreportsthatTEKEScon-tributed about 10% of Nokia’s research and development expenditure in 1991, even though the support has been declining over time – it was only 0.4% in 2004. The strategy of using governmentmoneytofinancetheprivatesectorispayingoff:Nokiacontributestotherestof the economy not only directly but also via its suppliers and the positive spillover from its research and development activities to other technology industries and to academia. Other sectors are actively endorsed, such as biosciences, but the results from that course of action are still to be seen.

Chapter 7 concludes by highlighting the challenges that Finland faces going forward. Un-employment is relatively high for an otherwise fairly successful economy, remaining above pre-crisis levels. The authors also underline issues common to other rich economies: popula-tion aging and the implications of facing an increasingly more open and competitive global economy. The book should prove illuminating for anyone interested in economic growth and development. But potential readers should be warned that there is no recipe in the book as to how other countries could follow Finland’s path to consolidating a technology-driven economy.

References

Honkapohja, Seppo, and Erkki A. Koskela (1999) The economic crisis of the 1990s in Fin-land, Economic Policy, vol. 29, pp. 401-436.

Sánchez-Fung, José R. (2005) Exchange rates, monetary policy, and interest rates in the Do-minican Republic during the 1990s boom and new millennium crisis, Journal of Latin Ameri-can Studies, vol. 37, pp. 727-738.

José R. Sánchez-FungKingston University, London, UK

83PhD news

PhD news

Management by values: analysis of influencing aspects and its theoretical and practical implications

Krista Jaakson

E-mail: [email protected] public defence of the dissertation took place at the Faculty of Economics and Business Administration of the University of Tartu on 12 November 2009 in Narva Rd. 4, Tartu The dissertation is available at the University of Tartu Library in Tartu, W.Struve 1, 50091 A full electronic version of the dissertation is available at http://dspace.utlib.ee/dspace/bitstream/10062/14186/1/jaakson_krista.pdf

Management by values is a concept that is applied in organisational practices in Estonia as wellasabroad.Therootsofthismanagementconceptlieinthe1980s,whensemi-scientificworks were published in the US, where organisations with a strong culture were claimed to be successful on the basis that a strong culture leads to higher behavioural consistency, stronger goal alignment, and increased employee effort. The core element of organisational culture consists of organisational values, and management by values is focused on these. The authorofthisthesisdefinesmanagementbyvaluesasaseriesofinterconnectedmanagerialactivities to ensure the acceptance of relevant organisational values inside and outside the organisation. While plenty of theoretical literature exists on management by values, empiri-cal research is scant.

The aim of this thesis was to work out theoretical and practical implications for management by values based on the example of Estonian organisations. The thesis consists of four sepa-ratearticlessupplementedbyanintroductoryoverviewoftheresearchfieldandadiscussionat the end. Four research questions were formulated: Which stakeholders, and how, should be engaged in defining values?, What socio-demographic variables affect the perception of values?, How are values and practices (using the example of corporate social responsibility) related?, and Why do values and practices diverge? Seventeen research propositions were set up to answer these questions.

Itwasfoundthatmanagementbyvaluesisinfluencedbyexistingpracticesoftheorganisa-tion, its stakeholders, availability of resources and employee empowerment, internal systems and organisational culture. In addition, the success of management by values is dependent on how well the values statement itself meets certain principles. Organisational members’ per-ceptionofvaluesasarelevantprocessinmanagementbyvaluesisalsoinfluencedbytheirsocio-demographic variables such as gender and involvement in the organisation. Conclu-sions reached in this thesis help managers to better understand the essence of management

84 Baltic Journal of Economics 10(1) (2010) 83-87

by values and raise awareness of potential problems that may occur in the process. Although empirical data are based on Estonian organisations, the author asserts that the results are of interest to and suggestions applicable in any organisation wishing to implement management by values.

85

Manifestations of organizationalculture basedon the example of estonian organizations

Anne Reino

E-mail: [email protected] public defence of the dissertation took place at the Faculty of Economics and Business Administration of the University of Tartu on November 6th, 2009 in Narva Rd 4, Oeconomicum, Tartu.The dissertation is available at the University of Tartu Library in Tartu, Str. W.Struve 1, 50091.A full electronic version of the dissertation is available at:http://dspace.utlib.ee/dspace/bitstream/10062/11016/1/reino_anne.pdf

Organizational culture facilitates explanation of the essence and meaning of the organiza-tionandhasbeenconsideredapowerfulforceinfluencingorganizationalbehaviourandtheoverall performance of organizations. The relevance of organizational culture as a topic is important in unpredictable and rapidly changing economic conditions, where the human side of organizations may be critical for their survival.

The aim of this dissertation was to outline regularities and patterns in manifestations of orga-nizational culture using the example of Estonian organizations. In the scope of the disserta-tionthenotionofanorganizationalculturepatternwasdefinedasaculturalprofilewhichcharacterizesorganizationalculturefromtwoperspectives:firstly, itdemonstratestherela-tive importance of organizational cultural types in a particular organization and secondly, it denotes the relationships between different organizational cultural types. The author of the dissertation analyzed what kinds of connection exist between types of organizational culture in Estonian organizations and how contextual factors such as national culture and industry influenceorganizationalculture.Thedissertationalsoanalyzedtheimpactoforganizationalcharacteristics - age and size - on patterns of organizational culture.

The dissertation aimed to broaden the scope of research into organizational culture in terms offactorsinfluencingmanifestationsoforganizationalculture.Itcouldbearguedthatagapexists between theoretical discussions about the formation of organizational culture and in-fluentialforcesinthatprocess,andempiricalresearchonthetopic.Althoughintheorysev-eralcontextualandorganizationalfactorsareseenasimportantdeterminantsthatinfluencemani festations of organizational culture, empirical research seldom focuses on those par-ticular factors (national culture could be seen as an exception here). Moreover, research into organizational culture has long traditions in Western countries, but no systematic overview and analysis of the topic has been carried out in transition countries like Estonia. Research conducted on organizational culture in Estonia has been quite fragmented, both in terms of samples and methods. Therefore, extensive research covering variables not yet investigated

PhD news

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and also considering the peculiarities of the local context is crucial to explore regularities in manifestations of organizational culture.

In order to analyze the impact of contextual and organizational factors on patterns of orga-nizational culture in Estonian organizations, a new tool for analyzing organizational culture

– an Organizational Values Questionnaire - was developed by the author. The general frame-work of the questionnaire was based on the ideas of the Competing Values Framework. Em-pirical research brought out several regularities in the manifestation of organizational culture. Those regularities were discussed in the context of Estonia.

Analysis of organizational culture showed a positive relationship between types of orga-nizational culture.Thisfindingdemonstrates that althoughcertain typesoforganizationalculture encompass antagonistic values on theoretical grounds, those values tend to coex-ist in organizations. Therefore, organizational culture should be approached as a continuum, where changes in some aspects involve changes in other aspects of organizational culture. The relationships that exist between types of organizational culture may demonstrate basic assumptions held by people in and around the organiza tion. For example, the current study indicated a moderate connection between the Rational Goal and Internal Processes types oforganizationalculture,afindingthatdiffersfrompreviousstudiesconductedindifferentculturalareas.ThisfindingmaybeinterpretedasareflectionofculturalvaluesinEstoniansociety, where it is believed that competitiveness requires internal integration and formaliza-tion.Moreover this result is quite similar tofindings from research conducted inEstoniasupporting the idea that Estonian organizations tend to follow the principles of a well-oiled machine. But emphasis on results and relying on formalization may also be connected to the transitional era in society. First of all, the period of transition forced organizations to become more results-oriented, but it also put pressure on people’s attitudes and behavioural patterns, wheresignificantchangeswereexpected.Newwaysofoperatingexpectedfromemployeesoften also necessitated new standards and proce dures, so that organizations going through important change processes became more formalized and bureaucratic.

The analysis demonstrated similarities in patterns of organizational culture in Estonian orga-nizations – it became evident that those types of organizational culture that value stability and control were dominant in patterns of organizational culture. Findings showed that the impact oftheindustrywheretheorganizationoperatedwasasignificantfactorinfluencingthecul-ture of the particular organization; moreover, the impact of the industry may be even more importantcomparedtotheinfluenceofnationalculture.Theresearchcouldnotconfirmtheeffect of organizational age on patterns of organizational culture. The results of the current research indicated that organizational age did not predict patterns of organizational culture. Thisfindingmayberelatedtothecontextoftransitionalcountriesbecausethedistinctionbetween old and new organizations is blurred due to radical changes in society and consid-ering the impact of those changes on organizations. Unlike organizational age, the research revealed the impact of organizational size on organizational culture.

The contribution of the dissertation is twofold: several implications of the disser tation ap-peared from the perspective of analysis of organizational culture, as well as from the view-point of management practices. Findings from the study could be taken into account when planning management action in organizations.


Anne-Marie och Gustaf Andersstiftelse för medieforskning

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